S6K1 amplification confers innate resistance to CDK4/6 inhibitors through activating c-Myc pathway in patients with estrogen receptor-positive breast cancer.

BACKGROUND: CDK4/6 inhibitors combined with endocrine therapy has become the preferred treatment approach for patients with estrogen receptor-positive metastatic breast cancer. However, the predictive biomarkers and mechanisms of innate resistance to CDK4/6 inhibitors remain largely unknown. We sought to elucidate the molecular hallmarks and therapeutically actionable features of patients with resistance to CDK4/6 inhibitors. METHODS: A total of 36 patients received palbociclib and endocrine therapy were included in this study as the discovery cohort. Next-generation sequencing of circulating tumour DNA in these patients was performed to evaluate somatic alterations associated with innate resistance to palbociclib. Then the candidate biomarker was validated in another independent cohort of 104 patients and publicly available datasets. The resistance was verified in parental MCF-7 and T47D cells, as well as their derivatives with small interfering RNA transfection and lentivirus infection. The relevant mechanism was examined by RNA sequencing, chromatin immunoprecipitation and luciferase assay. Patient-derived organoid and patient-derived xenografts studies were utilized to evaluated the antitumor activity of rational combinations. RESULTS: In the discovery cohort, S6K1 amplification (3/35, 9%) was identified as an important reason for innate resistance to CDK4/6 inhibitors. In the independent cohort, S6K1 was overexpressed in 15/104 (14%) patients. In those who had received palbociclib treatment, patients with high-expressed S6K1 had significantly worse progression free survival than those with low S6K1 expression (hazard ratio = 3.0, P = 0.0072). Meta-analysis of public data revealed that patients with S6K1 amplification accounted for 12% of breast cancers. Breast cancer patients with high S6K1 expression had significantly worse relapse-free survival (hazard ratio = 1.31, P < 0.0001). In breast cancer cells, S6K1 overexpression, caused by gene amplification, was sufficient to promote resistance to palbociclib. Mechanistically, S6K1 overexpression increased the expression levels of G1/S transition-related proteins and the phosphorylation of Rb, mainly through the activation of c-Myc pathway. Notably, this resistance could be abrogated by the addition of mTOR inhibitor, which blocked the upstream of S6K1, in vitro and in vivo. CONCLUSIONS: S6K1 amplification is an important mechanism of innate resistance to palbociclib in breast cancers. Breast cancers with S6K1 amplification could be considered for combinations of CDK4/6 and S6K1 antagonists.

Spectral Tensor Layers for Communication-Free Distributed Deep Learning.

In this article, we propose a novel spectral tensor layer for communication-free distributed deep learning. The overall framework is as follows: first, we represent the data in tensor form (instead of vector form) and replace the matrix product in conventional neural networks with the tensor product, which in effect imposes certain transformed-induced structure on the original weight matrices, e.g., a block-circulant structure; then, we apply a linear transform along a certain dimension to split the original dataset into multiple spectral subdatasets; as a result, the proposed spectral tensor network consists of parallel branches where each branch is a conventional neural network trained on a spectral subdataset with ZERO communication cost. The parallel branches are directly ensembled (i.e., the weighted sum of their outputs) to generate an overall network with substantially stronger generalization capability than that of each branch. Moreover, the proposed method enjoys a byproduct of decentralization gain in terms of memory and computation, compared with traditional networks. It is a natural yet elegant solution for heterogeneous data in federated learning (FL), where data at different nodes have different resolutions. Finally, we evaluate the proposed spectral tensor networks on the MNIST, CIFAR-10, ImageNet-1K, and ImageNet-21K datasets, respectively, to verify that they simultaneously achieve communication-free distributed learning, distributed storage reduction, parallel computation speedup, and learning with multiresolution data.

Hypergraph Isomorphism Computation.

The isomorphism problem, crucial in network analysis, involves analyzing both low-order and high-order structural information. Graph isomorphism algorithms focus on structural equivalence to simplify solver space, aiding applications like protein design, chemical pathways, and community detection. However, they fall short in capturing complex high-order relationships, unlike hypergraph isomorphism methods. Traditional hypergraph methods face challenges like high memory use and inaccurate identification, leading to poor performance. To overcome these, we introduce a hypergraph Weisfeiler-Lehman (WL) test algorithm, extending the WL test from graphs to hypergraphs, and develop a hypergraph WL kernel framework with two variants: the Hypergraph WL Subtree Kernel and Hypergraph WL Hyperedge Kernel. The Hypergraph WL Subtree Kernel counts different types of rooted subtrees and generates the final feature vector for a given hypergraph by comparing the number of different types of rooted subtrees. The Subtree Kernel identifies different rooted subtrees, while the Hyperedge Kernel focuses on hyperedges' vertex labels, enhancing feature vector generation. In order to fulfill our research objectives, a comprehensive set of experiments was meticulously designed, including seven graph classification datasets and 12 hypergraph classification datasets. Results on graph classification datasets indicate that the Hypergraph WL Subtree Kernel can achieve the same performance compared with the classical Graph Weisfeiler-Lehman Subtree Kernel. Results on hypergraph classification datasets show significant improvements compared to other typical kernel-based methods, which demonstrates the effectiveness of the proposed methods. In our evaluation, our proposed methods outperform the second-best method in terms of runtime, running over 80 times faster when handling complex hypergraph structures. This significant speed advantage highlights the great potential of our methods in real-world applications.

Neoadjuvant targeted immunotherapy followed by surgical resection versus upfront surgery for hepatocellular carcinoma with macrovascular invasion: A multicenter study.

Background: This study aimed to investigate the safety and efficacy of preoperative targeted immunotherapy followed by surgical resection for hepatocellular carcinoma (HCC) patients with macrovascular invasion. Method: Clinical information of HCC patients with macrovascular invasion was collected from four medical centers. These patients were divided into two cohorts: the upfront surgery group (n=40) and the neoadjuvant group (n=22). Comparisons between the two groups were made with appropriate statistical methods. Results: HCC Patients with macrovascular invasion in the neoadjuvant group were associated with increased incidence of postoperative ascites (72.73% vs. 37.5%, P=0.008), but shorter postoperative hospital stay (10 days vs. 14 days, P=0.032). Furthermore, targeted immunotherapy followed by surgical resection significantly reduced the postoperative recurrence rate at both 3 months and 1 year (9% versus 28.9%, 32.1% versus 67.9%, respectively; P=0.018), but increased the postoperative nononcologic mortality rate within 1 year (20.1% vs. 2.8%; P= 0.036). Conclusion: For HCC patients with macrovascular invasion, preoperative targeted immunotherapy significantly decreased the postoperative tumor recurrence rate while maintaining relative safety, but such a treatment may also result in chronic liver damage and increased risk of nononcologic mortality.

Dysregulation in IFN-γ signaling and response: the barricade to tumor immunotherapy.

Interferon-gamma (IFN-γ) has been identified as a crucial factor in determining the responsiveness to immunotherapy. Produced primarily by natural killer (NK) and T cells, IFN-γ promotes activation, maturation, proliferation, cytokine expression, and effector function in immune cells, while simultaneously inducing antigen presentation, growth arrest, and apoptosis in tumor cells. However, tumor cells can hijack the IFN-γ signaling pathway to mount IFN-γ resistance: rather than increasing antigenicity and succumbing to death, tumor cells acquire stemness characteristics and express immunosuppressive molecules to defend against antitumor immunity. In this review, we summarize the potential mechanisms of IFN-γ resistance occurring at two critical stages: disrupted signal transduction along the IFNG/IFNGR/JAK/STAT pathway, or preferential expression of specific interferon-stimulated genes (ISGs). Elucidating the molecular mechanisms through which tumor cells develop IFN-γ resistance help identify promising therapeutic targets to improve immunotherapy, with broad application value in conjugation with targeted, antibody or cellular therapies.

Proteasome-dependent senescent tumor cells mediate immunosuppression through CCL20 secretion and M2 polarization in pancreatic ductal adenocarcinoma.

The outcome of pancreatic ductal adenocarcinoma (PDAC) remains poor due to few therapeutic options available and challenges with precision therapy to target each tumour's specific characteristics. In this study, a biologically meaningful patient stratification-prognostic model with therapeutic suggestion value based on tumor senescence was developed and validated in multiple independent cohorts. Further mechanistic investigation based on single-cell transcriptomic data and in vitro experiments revealed that complement derived from non-senescent tumor cells stimulates M1 differentiation and antigen presentation, while senescent tumor cells secrete CCL20 to favor immunosuppressive M2 polarization. Also, senescent phenotype depends on proteasome function, suggesting that high-risk, high-senescence patients may benefit from proteasome inhibitors, which reverse senescence-mediated resistance to conventional chemotherapy and improve outcome. In conclusion, the current study identified senescence as a tumor-specific, hazardous factor associated with immunosuppression in PDAC. Mechanistically, senescence abrogates complement-induced M1 activation and antigen presentation, and upregulates CCL20 to favor M2 polarization. The senescence-related risk model is prognostic and therapeutic-suggestive. In light of the reliance of senescent cells on proteasomal functions, proteasome inhibitors are promising agents for high-risk patients with senescent PDAC.

Dynamic polarization of tumor-associated macrophages and their interaction with intratumoral T cells in an inflamed tumor microenvironment: from mechanistic insights to therapeutic opportunities.

Immunotherapy has brought a paradigm shift in the treatment of tumors in recent decades. However, a significant proportion of patients remain unresponsive, largely due to the immunosuppressive tumor microenvironment (TME). Tumor-associated macrophages (TAMs) play crucial roles in shaping the TME by exhibiting dual identities as both mediators and responders of inflammation. TAMs closely interact with intratumoral T cells, regulating their infiltration, activation, expansion, effector function, and exhaustion through multiple secretory and surface factors. Nevertheless, the heterogeneous and plastic nature of TAMs renders the targeting of any of these factors alone inadequate and poses significant challenges for mechanistic studies and clinical translation of corresponding therapies. In this review, we present a comprehensive summary of the mechanisms by which TAMs dynamically polarize to influence intratumoral T cells, with a focus on their interaction with other TME cells and metabolic competition. For each mechanism, we also discuss relevant therapeutic opportunities, including non-specific and targeted approaches in combination with checkpoint inhibitors and cellular therapies. Our ultimate goal is to develop macrophage-centered therapies that can fine-tune tumor inflammation and empower immunotherapy.

Tumor senescence leads to poor survival and therapeutic resistance in human breast cancer.

Background: Breast cancer (BRCA) is the most common malignant tumor that seriously threatens the health of women worldwide. Senescence has been suggested as a pivotal player in the onset and progression of tumors as well as the process of treatment resistance. However, the role of senescence in BRCA remains unelucidated. Methods: The clinical and transcriptomic data of 2994 patients with BRCA were obtained from The Cancer Genome Atlas and the METABRIC databases. Consensus clustering revealed senescence-associated subtypes of BRCA patients. Functional enrichment analysis explored biological effect of senescence. We then applied weighted gene co-expression network analysis (WGCNA) and LASSO regression to construct a senescence scoring model, Sindex. Survival analysis validated the effectiveness of Sindex to predict the overall survival (OS) of patients with BRCA. A nomogram was constructed by multivariate Cox regression. We used Oncopredict algorithm and real-world data from clinical trials to explore the value of Sindex in predicting response to cancer therapy. Results: We identified two distinct senescence-associated subtypes, noted low senescence CC1 and high senescence CC2. Survival analysis revealed worse OS associated with high senescence, which was also validated with patient samples from the National Cancer Center in China. Further analysis revealed extensively cell division and suppression of extracellular matrix process, along with lower stromal and immune scores in the high senescence CC2. We then constructed a 37 signature gene scoring model, Sindex, with robust predictive capability in patients with BRCA, especially for long time OS beyond 10 years. We demonstrated that the Sene-high subtype was resistant to CDK inhibitors but sensitive to proteosome inhibitors, and there was no significant difference in paclitaxel chemotherapy and immunotherapy between patients with different senescence statuses. Conclusions: We reported senescence as a previously uncharacterized hallmark of BRCA that impacts patient outcomes and therapeutic response. Our analysis demonstrated that the Sindex can be used to identify not only patients at different risk levels for the OS but also patients who would benefit from some cancer therapeutic drugs.

Multifaceted roles of T cells in obesity and obesity-related complications: A narrative review.

Obesity is characterized by chronic low-grade inflammatory responses in the adipose tissue, accompanied by pronounced insulin resistance and metabolic anomalies. It affects almost all body organs and eventually leads to diseases such as fatty liver disease, type 2 diabetes mellitus, and atherosclerosis. Recently, T cells have emerged as interesting therapeutic targets because the dysfunction of T cells and their cytokines in the adipose tissue is implicated in obesity-induced inflammation and their complicated onset. Although several recent narrative reviews have provided a brief overview of related evidence in this area, they have mainly focused on either obesity-associated T cell metabolism or modulation of T cell activation in obesity. Moreover, at present, no published review has reported on the multifaceted roles of T cells in obesity and obesity-related complications, even though there has been a significant increase in studies on this topic since 2019. Therefore, this narrative review aims to comprehensively summarize current advances in the mechanistic roles of T cells in the development of obesity and its related complications. Further, we aim to discuss relevant drugs for weight loss as well as the contradictory role of T cells in the same disease so as to highlight key findings regarding this topic and provide a valid basis for future treatment strategies.

High SURF4 expression is associated with poor prognosis of breast cancer.

SURF4 has been suggested as an oncogene in cancer. However, the role of SURF4 in breast cancer has not been demonstrated yet. The data were obtained from TCGA database and 1104 patients were analyzed using bioinformatics analysis. SURF4 is significantly (P < 0.001) highly expressed in tumor. High expression of SURF4 was observed in T4, infiltrating ductal carcinoma, ER negative, PR negative, and HER2 positive, female, patients without lymph node metastasis, HER2 overexpression type, and deceased patients. As for characteristics correlated with high expression of SURF4, gender, histological type, molecular subtype, ER, PR, HER2, and vital status exhibited significant differences. The age (HR: 2.317, P < 0.001), stage (HR: 2.090, P < 0.001), and SURF4 expression (HR: 1.958, P = 0.005) exhibited independent prognostic value for overall survival (OS). Patients with high SURF4 expression, higher age, equivocal HER2, higher stages, or positive margin status had shorter OS. The stage (HR: 1.579, P < 0.001), and margin status (HR: 1.463, P = 0.006) exhibited independent prognostic value for relapse-free survival of breast cancer. High expression of SURF4 was first found in breast cancer. High SURF4 expression was observed in breast cancer tissue and cell. SURF4 promoted the proliferation and migration of 4T1 cells. SURF4 may be a biomarker in diagnosis and prognosis of breast cancer.

Advances in the study of RNA-binding proteins in diabetic complications.

BACKGROUND: It has been reported that diabetes mellitus affects 435 million people globally as a primary health care problem. Despite many therapies available, many diabetes remains uncontrolled, giving rise to irreversible diabetic complications that pose significant risks to patients' wellbeing and survival. SCOPE OF REVIEW: In recent years, as much effort is put into elucidating the posttranscriptional gene regulation network of diabetes and diabetic complications; RNA binding proteins (RBPs) are found to be vital. RBPs regulate gene expression through various post-transcriptional mechanisms, including alternative splicing, RNA export, messenger RNA translation, RNA degradation, and RNA stabilization. MAJOR CONCLUSIONS: Here, we summarized recent studies on the roles and mechanisms of RBPs in mediating abnormal gene expression in diabetes and its complications. Moreover, we discussed the potential and theoretical basis of RBPs to treat diabetes and its complications.

FOXO3-induced oncogenic lncRNA CASC9 enhances gefitinib resistance of non-small-cell lung cancer through feedback loop.

Gefitinib is tyrosine kinase inhibitor of epidermal growth factor receptor, which exhibits notable clinical efficacy in non-small-cell lung cancer (NSCLC) treatment. However, gefitinib resistance is a critical obstacle for NSCLC targeted therapy. Here, we investigated the biological functions and mechanisms of lncRNA CASC9 in NSCLC gefitinib resistance. Screening analysis and RT-qPCR demonstrated that CASC9 was up-regulated in the gefitinib-resistant NSCLC cells (PC9/GR). Moreover, high-expression of CASC9 acted as an unfavorable factor for NSCLC patients. Functionally, CASC9 promoted the proliferation and gefitinib resistance of PC9/GR cells in vitro, and knockdown of CASC9 repressed the tumor growth in vivo. Mechanistically, CASC9 epigenetically promoted the FOXO3 expression via inhibiting miR-195-5p. In turn, transcription factor FOXO3 bound with the promoter region of CASC9 to enhance CASC9 transcriptional level, thereby forming CASC9/miR-195-5p/FOXO3 positive feedback loop. In conclusion, our research identified the regulation of CASC9/miR-195-5p/FOXO3 feedback loop on NSCLC gefitinib resistance, which might help researchers develop potential therapeutic targets for NSCLC.

Progression Risk Assessment of Post-surgical Papillary Thyroid Carcinoma Based on Circular RNA-Associated Competing Endogenous RNA Mechanisms.

Background: Accurate risk assessment of post-surgical progression in papillary thyroid carcinoma (PTC) patients is critical. Exploring key differentially expressed mRNAs (DE-mRNAs) regulated by differentially expressed circular RNAs (circRNAs) via the ceRNA mechanism could help establish a novel assessment tool. Methods: ceRNA network was established based on differentially expressed RNAs and correlation analysis. DE-mRNAs within the ceRNA network associated with progression-free interval (PFI) of PTC were identified to construct a prognostic ceRNA regulatory subnetwork. least absolute shrinkage and selection operator (LASSO)-Cox regression was applied to identify hub DE-mRNAs and establish a novel DE-mRNA signature in predicting PFI of PTC. Results: Six hub DE-mRNAs, namely, CLCNKB, FXBO27, FXYD6, RIMS2, SPC24, and CDKN2A, were identified to be most significantly related to the PFI of PTC, and a prognostic DE-mRNA signature was proposed. A nomogram incorporating the DE-mRNA signature and clinical parameters was established to improve the progression risk assessment in post-surgical PTC, which was superior to the American Thyroid Association risk stratification system and distant Metastasis, patient Age, Completeness of resection, local Invasion, and tumor Size (MACIS) score American Joint Committee on Cancer staging system. Conclusions: Based on the circRNA-associated ceRNA RNA mechanism, a DE-mRNA signature and prognostic nomogram was established, which may improve the progression risk assessment in post-surgical PTC.