Molecular Oncology最新文献

Glioblastoma (GB) is the most aggressive primary brain tumor with poor prognosis despite multimodal therapy. Calorie-restricted diets have emerged as putative strategies to augment anticancer therapies. We employed UHPLC-high-resolution mass spectrometry analyses of plasma lipids and polar metabolites to assess the systemic metabolic effects of a 72-h preoperative fasting period in IDH-wild-type glioma patients (n = 9 GB and n = 1 diffuse pediatric-type high-grade H3/IDH-wildtype) who participated in the prospective ERGO3 trial (NCT04461938). Fasting reduced lysophosphatidylcholines (LPC, LPC-O), lysophosphatidylethanolamines (LPE, LPE-O), and increased free fatty acids and carnitines. Triglyceride (TG) profiles shifted from short-chain TGs (42-48 C-atoms) to very long-chain TGs (58-60 C-atoms) indicating an exploitation of neutral lipid stores. Branched-chain amino acids, aminobutyric acid, and uric acids were increased, and glucose reduced after fasting. The effects of fasting were comparable in men and women. To our knowledge, this is the first study that evaluated the effects of fasting on systemic lipid/metabolite levels in GB patients. Our results may hold promise for integrating fasting interventions as a component of a potential metabolic tumor therapy.

Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease. Several studies have identified transcriptional subtypes of mCRPC, but comprehensive analysis of prognostic gene expression pathways has been limited. Therefore, we aggregated a cohort of 1012 mCRPC tissue samples from 769 patients and investigated the association of gene expression-based pathways with clinical outcomes and intrapatient and intratumor heterogeneity. Survival data were obtained for 272 patients. Pathway-level enrichment was evaluated using gene set variation analysis. scRNA-seq datasets from mCRPC tissue biopsies and circulating tumor cells were used to investigate heterogeneity of adverse pathways. We identified five pathway clusters: (a) Immune response/WNT/TGF-beta signaling, (b) AR signaling/luminal signatures, (c) mTOR signaling and glycolysis, (d) cell proliferation, and (e) neuroendocrine differentiation. Proliferation, AR signaling loss, and glycolysis/mTOR signaling were independently prognostic. Adverse prognostic pathway scores decreased on treatment with AR signaling inhibitors, but not at progression, suggesting failure to permanently target these pathways. scRNA-seq datasets from mCRPC tissue biopsies and circulating tumor cells were used to investigate heterogeneity of adverse pathways. Our results suggest loss of AR signaling, high proliferation, and a glycolytic phenotype as adverse prognostic pathways in mCRPC that could be used in conjunction with clinical factors to prognosticate for treatment decisions.

Patient engagement in healthcare and research empowers patients to actively participate in decision-making, treatment planning, and research design, fostering better treatment outcomes and relevance. However, barriers, such as power imbalances, structural limitations, a lack of awareness, and socioeconomic disparities, often hinder meaningful involvement, particularly for marginalized groups. Overcoming these challenges requires inclusive frameworks and infrastructures to promote collaboration among patients, researchers, and other stakeholders. Initiatives like the Patient Engagement Open Forum or World Cancer Research Day underscore the importance of patient-centered approaches. By fostering trust, transparency, and shared decision-making, a more inclusive and impactful healthcare and research ecosystem can be achieved.

In hereditary papillary renal cell carcinoma (HPRCC), the hepatocyte growth factor receptor (MET) receptor tyrosine kinase (RTK) mutations recorded to date are located in the kinase domain and lead to constitutive MET activation. This contrasts with MET mutations identified in non-small-cell lung cancer (NSCLC), which lead to exon 14 skipping and deletion of a regulatory domain: In this latter case, the mutated receptor still requires ligand stimulation. Sequencing of MET in samples from 158 HPRCC and 2808 NSCLC patients revealed 10 uncharacterized mutations. Four of these, all found in HPRCC and leading to amino acid substitutions in the N-lobe of the MET kinase, proved able to induce cell transformation, which was further enhanced by hepatocyte growth factor (HGF) stimulation: His1086Leu, Ile1102Thr, Leu1130Ser, and Cis1125Gly. Similar to the variant resulting in MET exon 14 skipping, the two N-lobe MET variants His1086Leu and Ile1102Thr were found to require stimulation by HGF in order to strongly activate downstream signaling pathways and epithelial cell motility. The Ile1102Thr mutation also displayed transforming potential, promoting tumor growth in a xenograft model. In addition, the N-lobe-mutated MET variants were found to trigger a common HGF-stimulation-dependent transcriptional program, consistent with an observed increase in cell motility and invasion. Altogether, this functional characterization revealed that N-lobe variants still require ligand stimulation, in contrast to other RTK variants. This suggests that HGF expression in the tumor microenvironment is important for tumor growth. The sensitivity of these variants to MET inhibitors opens the way for use of targeted therapies for patients harboring the corresponding mutations.

Prognostic transcriptomic signatures for prostate cancer (PCa) often overlook the cellular origin of expression changes, an important consideration given the heterogeneity of the disorder. Current clinicopathological factors inadequately predict biochemical recurrence, a critical indicator guiding post-treatment strategies following radical prostatectomy. To address this, we conducted a meta-analysis of four large-scale PCa datasets and found 33 previously reported PCa-associated genes to be consistently up-regulated in prostate tumours. By analysing single-cell RNA-sequencing data, we found these genes predominantly as markers in epithelial cells. Subsequently, we applied 97 advanced machine-learning algorithms across five PCa cohorts and developed an 11-gene epithelial expression signature. This signature robustly predicted biochemical recurrence-free survival (BCRFS) and stratified patients into distinct risk categories, with high-risk patients showing worse survival and altered immune cell populations. The signature outperformed traditional clinical parameters in larger cohorts and was overall superior to published PCa signatures for BCRFS. By analysing peripheral blood data, four of our signature genes showed potential as biomarkers for radiation response in patients with localised cancer and effectively stratified castration-resistant patients for overall survival. In conclusion, this study developed a novel epithelial gene-expression signature that enhanced BCRFS prediction and enabled effective risk stratification compared to existing clinical- and gene-expression-derived prognostic tools. Furthermore, a set of genes from the signature demonstrated potential utility in peripheral blood, a tissue amenable to minimally invasive sampling in a primary care setting, offering significant prognostic value for PCa patients without requiring a tumour biopsy.

Nasopharyngeal carcinoma (NPC) is a kind of malignant tumor with high metastasis. Circular RNAs (circRNAs) are involved in tumor progression, but their functions and mechanisms are not well understood. Vasculogenic mimicry (VM) has been discovered as an alternative way to supply tumor nutrition and accelerate tumor progression, including NPC. We previously found that circCCNB1 (derived from cyclin B1) could inhibit the migration and invasion of NPC cells by binding to nuclear factor 90 (NF90), however, whether circCCNB1 has additional biological functions is still unclear. In this study, the effects of circCCNB1 binding to NF90 on the generation of miR-15b-5p and miR-7-1-3p were detected using qRT-PCR, western blotting, RNA pulldown, ribonucleoprotein immunoprecipitation and truncated experiments. VM formation assays were used to assess their biological functions. We found that circCCNB1 promoted the processing and generation of miR-15b-5p and miR-7-1-3p through competitive binding to NF90, thereby inhibiting the expression of calumenin (CALU), kinesin family member 1B (KIF1B), RNA polymerase III subunit G (POLR3G), ultimately decreasing the VM of NPC cells. This study not only reveals a new function of circCCNB1 in NPC, but also provides new insights for targeting angiogenesis therapy.

Immune status critically affects cancer progression and therapy responses. This study aimed to identify plasma proteome changes in immunosuppressive cancer and potential biomarkers predicting systemic immunosuppression. Mouse models of syngeneic breast tumors (benign 67NR and malignant 4T1) were used to collect plasma samples. Plasma samples from naive mice and both early- and late-stage tumor-bearing mice were subjected to liquid chromatography-mass spectrometry (LC-MS) analysis. 4T1-bearing mice showed systemic immunosuppression characterized by significant generation of myeloid-derived suppressor cells (MDSCs) as early as 7 days after tumor implantation, unlike 67NR tumors. LC-MS identified 1086 proteins across the five experimental groups, with 27 proteins showing group-specific expression in 4T1 blood compared with 67NR blood. Immune-related proteins osteopontin, lactotransferrin, calreticulin, and peroxiredoxin 2 were selected as potential biomarkers of MDSC-producing breast cancer. These markers were expressed in cancer cells or MDSC in the 4T1 model, and osteopontin and peroxiredoxin 2 were associated with low survival probability and high recurrence in patients with triple-negative breast cancer. Our findings suggest that MDSC-producing immunosuppressive cancers have unique plasma proteomes, offering additional insights into cancer immune status.

Acute myeloid leukemia (AML) is a heterogeneous cancer, making outcomes prediction challenging. Several predictive and prognostic models are used but have considerable inaccuracy at individual level. We tried to increase prediction accuracy using a multi-omics strategy. We interrogated data from 1391 consecutive, newly diagnosed subjects with AML, integrating information on mutation topography, DNA methylation, and transcriptomics. We developed an unsupervised multi-omics classification system (UAMOCS) with these data. UAMOCS provides a multidimensional understanding of AML heterogeneity and stratifies subjects into three cohorts: (a) UAMOCS1 [high lymphocyte activating 3 (LAG3) expression, chromosome instability, myelodysplasia-related mutations]; (b) UAMOCS2 (monocytic-like profile, immune suppression and activated angiogenesis and hypoxia pathways); and (c) UAMOCS3 [CCAAT enhancer binding protein alpha (CEBPA) mutations and MYC pathway activation]. UAMOCS distinguishes overall survival rates across the cohorts (TCGA P = 0.042; GSE71014 P = 0.043; ihCAMs-AML, GSE102691 and GSE37642 all P < 0.001). The model's C-statistic is comparable to the 2022 ELN risk classification (0.87 vs 0.82; P = 0.162), but offers a more nuanced distinction between intermediate- and high-risk groups. When combined with high-throughput drug sensitivity testing, UAMOCS can accurately predict sensitivity to azacitidine (AZA) and venetoclax. The UAMOCS system is available as an R package. The UAMOCS system has the potential to redefine AML subtypes, enhance prognostic predictions, and guide treatment strategies based on patients' immune status and expected responses to therapies.

The National Cancer Institute (NCI) supports numerous research consortia that rely on imaging technologies to study cancerous tissues. To foster collaboration and innovation in this field, the Image Analysis Working Group (IAWG) was created in 2019. As multiplexed imaging techniques grow in scale and complexity, more advanced computational methods are required beyond traditional approaches like segmentation and pixel intensity quantification. In 2022, the IAWG held a virtual hackathon focused on addressing challenges in analyzing complex, high-dimensional datasets from fixed cancer tissues. The hackathon addressed key challenges in three areas: (1) cell type classification and assessment, (2) spatial data visualization and translation, and (3) scaling image analysis for large, multi-terabyte datasets. Participants explored the limitations of current automated analysis tools, developed potential solutions, and made significant progress during the hackathon. Here we provide a summary of the efforts and resultant resources and highlight remaining challenges facing the research community as emerging technologies are integrated into diverse imaging modalities and data analysis platforms.

Etoposide is an inhibitor of DNA topoisomerase II, an enzyme essential for DNA transcription, replication, and chromosome segregation. It is well accepted that etoposide triggers cell death due to DNA damage. Our results indicate that multiple molecular mechanisms contribute to etoposide-induced apoptosis, including the overexpression of the mitochondrial voltage-dependent anion channel 1 (VDAC1) and its oligomerization, forming a mega-channel that releases pro-apoptotic proteins, thereby activating apoptosis. Etoposide induces C-terminal truncation of VDAC1 (VDAC1-ΔC) via the proteolytic actions of calpain-1 and asparagine endopeptidase (AEP). A calpain-specific inhibitor effectively prevented etoposide-induced VDAC1-ΔC formation, apoptosis, and the nuclear translocation of apoptosis-inducing factor (AIF). Additionally, etoposide upregulates the expression levels of apoptosis regulators (p53, Bax, p21, AIF) and of the proteases calpain and AEP. Etoposide-induced apoptosis and VDAC1 truncation are cell-type dependent and associated with calpain levels and activity. Etoposide-induced VDAC1-ΔC formation and apoptosis are tightly linked: as both display similar patterns of concentration- and time-dependence, both are inhibited by calpain and AEP inhibitors, as well as the VDAC1 oligomerization inhibitor VBIT-4, and are dependent on intracellular Ca²⁺. These findings highlight the complexity of etoposide's actions in different cellular contexts, suggest possible mechanisms of resistance, offer potential biomarkers for guiding etoposide treatment in cancer patients, and propose targeting VDAC1 and calpain as promising therapeutic strategies in cancer therapy.