Novel prognostic biomarker TBC1D1 is associated with immunotherapy resistance in gliomas.

Background: Glioma, an aggressive brain tumor, poses a challenge in understanding the mechanisms of treatment resistance, despite promising results from immunotherapy. Methods: We identified genes associated with immunotherapy resistance through an analysis of The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) databases. Subsequently, qRT-PCR and western blot analyses were conducted to measure the mRNA and protein levels of TBC1 Domain Family Member 1 (TBC1D1), respectively. Additionally, Gene Set Enrichment Analysis (GSEA) was employed to reveal relevant signaling pathways, and the expression of TBC1D1 in immune cells was analyzed using single-cell RNA sequencing (scRNA-seq) data from GEO database. Tumor Immune Dysfunction and Exclusion (TIDE) database was utilized to assess T-cell function, while Tumor Immunotherapy Gene Expression Resource (TIGER) database was employed to evaluate immunotherapy resistance in relation to TBC1D1. Furthermore, the predictive performance of molecules on prognosis was assessed using Kaplan-Meier plots, nomograms, and ROC curves. Results: The levels of TBC1D1 were significantly elevated in tumor tissue from glioma patients. Furthermore, high TBC1D1 expression was observed in macrophages compared to other cells, which negatively impacted T cell function, impaired immunotherapy response, promoted treatment tolerance, and led to poor prognosis. Inhibition of TBC1D1 was found to potentially synergistically enhance the efficacy of immunotherapy and prolong the survival of cancer patients with gliomas. Conclusion: Heightened expression of TBC1D1 may facilitate an immunosuppressive microenvironment and predict a poor prognosis. Blocking TBC1D1 could minimize immunotherapy resistance in cancer patients with gliomas.

LXA4 protected mice from renal ischemia/reperfusion injury by promoting IRG1/Nrf2 and IRAK-M-TRAF6 signal pathways.

Excessive inflammatory response and increased oxidative stress play an essential role in the pathophysiology of ischemia/reperfusion (I/R)-induced acute kidney injury (IRI-AKI). Emerging evidence suggests that lipoxin A4 (LXA4), as an endogenous negative regulator in inflammation, can ameliorate several I/R injuries. However, the mechanisms and effects of LXA4 on IRI-AKI remain unknown. In this study, A bilateral renal I/R mouse model was used to evaluate the role of LXA4 in wild-type, IRG1 knockout, and IRAK-M knockout mice. Our results showed that LXA4, as well as 5-LOX and ALXR, were quickly induced, and subsequently decreased by renal I/R. LXA4 pretreatment improved renal I/R-induced renal function impairment and renal damage and inhibited inflammatory responses and oxidative stresses in mice kidneys. Notably, LXA4 inhibited I/R-induced the activation of TLR4 signal pathway including decreased phosphorylation of TAK1, p36, and p65, but did not affect TLR4 and p-IRAK-1. The analysis of transcriptomic sequencing data and immunoblotting suggested that innate immune signal molecules interleukin-1 receptor-associated kinase-M (IRAK-M) and immunoresponsive gene 1 (IRG1) might be the key targets of LXA4. Further, the knockout of IRG1 or IRAK-M abolished the beneficial effects of LXA4 on IRI-AKI. In addition, IRG1 deficiency reversed the up-regulation of IRAK-M by LXA4, while IRAK-M knockout had no impact on the IRG1 expression, indicating that IRAK-M is a downstream molecule of IRG1. Mechanistically, we found that LXA4-promoted IRG1-itaconate not only enhanced Nrf2 activation and increased HO-1 and NQO1, but also upregulated IRAK-M, which interacted with TRAF6 by competing with IRAK-1, resulting in deactivation of TLR4 downstream signal in IRI-AKI. These data suggested that LXA4 protected against IRI-AKI via promoting IRG1/Itaconate-Nrf2 and IRAK-M-TRAF6 signaling pathways, providing the rationale for a novel strategy for preventing and treating IRI-AKI.

An immune-related prognostic gene ULBP2 is correlated with immunosuppressive tumor microenvironment and immunotherapy in breast cancer.

Breast cancer (BC) is one of the major dangerous tumors threatening women's lives. We here aimed to sort out prognostic immune-related genes by univariate Cox regression analysis and build a model of immune-related genes for forecasting the prognosis of BC patients. We identified UL16 binding protein 2 (ULBP2) as a valuable gene for study in the model using related databases and algorithms analysis. We found the stromal and immune cells scores were higher in ULBP2 high expression group and ULBP2 was related to kinds of immune cells, most importantly had negative correlation with CD8+ T cell. Notably, ULBP2 was positively correlated with tumor mutational burden (TMB) and had relationship with many immune checkpoints. Correlation analysis revealed that ULBP2 expression was closely linked to the clinicopathological characters and negatively related to BC patient survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed the functional enrichment of differential genes related to ULBP2. Gene Set Enrichment Analysis (GSEA) indicated pathway enrichment in ULBP2 high and low expression groups. In short, this study comprehensively investigated the potential function of ULBP2 in BC, which might make ULBP2 to be an important therapeutic target for BC.

Aldehyde dehydrogenase 2-mediated aldehyde metabolism promotes tumor immune evasion by regulating the NOD/VISTA axis.

BACKGROUND: Aldehyde dehydrogenase 2 (ALDH2) is a crucial enzyme involved in endogenous aldehyde detoxification and has been implicated in tumor progression. However, its role in tumor immune evasion remains unclear. METHODS: Here, we analyzed the relationship between ALDH2 expression and antitumor immune features in multiple cancers. ALDH2 knockout tumor cells were then established using CRISPR/Cas9 system. In immunocompetent breast cancer EMT6 and melanoma B16-F10 mouse models, we investigated the impact of ALDH2 blockade on cytotoxic T lymphocyte function and tumor immune microenvironment by flow cytometry, mass cytometry, Luminex liquid suspension chip detection, and immunohistochemistry. Furthermore, RNA sequencing, flow cytometry, western blot, chromatin immunoprecipitation assay, and luciferase reporter assays were employed to explore the detailed mechanism of ALDH2 involved in tumor immune evasion. Lastly, the synergistic therapeutic efficacy of blocking ALDH2 by genetic depletion or its inhibitor disulfiram in combination with immune checkpoint blockade (ICB) was investigated in mouse models. RESULTS: In our study, we uncovered a positive correlation between the expression level of ALDH2 and T-cell dysfunction in multiple cancers. Furthermore, blocking ALDH2 significantly suppressed tumor growth by enhancing cytotoxic activity of CD8+ T cells and reshaping the immune landscape and cytokine milieu of tumors in vivo. Mechanistically, inhibiting ALDH2-mediated metabolism of aldehyde downregulated the expression of V-domain Ig suppressor of T-cell activation (VISTA) via inactivating the nucleotide oligomerization domain (NOD)/nuclear factor kappa-B (NF-κB) signaling pathway. As a result, the cytotoxic function of CD8+ T cells was revitalized. Importantly, ALDH2 blockade markedly reinforced the efficacy of ICB treatment. CONCLUSIONS: Our data delineate that ALDH2-mediated aldehyde metabolism drives tumor immune evasion by activating the NOD/NF-κB/VISTA axis. Targeting ALDH2 provides an effective combinatorial therapeutic strategy for immunotherapy.

An Assessment of Relations between Vegetation Green FPAR and Vegetation Indices through a Radiative Transfer Model.

The fraction of absorbed photosynthetically active radiation (FPAR) is widely used in remote sensing-based production models to estimate gross or net primary production. The forest canopy is composed primarily of photosynthetically active vegetation (PAV, green leaves) and non-photosynthetic vegetation (NPV e.g., branches), which absorb PAR but only the PAR absorbed by PAV is used for photosynthesis. Green FPAR (the fraction of PAR absorbed by PAV) is essential for the accurate estimation of GPP. In this study, the scattering by arbitrary inclined leaves (SAIL) model was reconfigured to partition the PAR absorbed by forest canopies. The characteristics of green FPAR and its relationships with spectral vegetation indices (NDVI, EVI, EVI2, and SAVI) were analyzed. The results showed that green FPAR varied with the canopy structure. In the forests with high coverage, the green FPAR was close to the total FPAR, while in the open forests, the green FPAR was far smaller than the total FPAR. Plant area index had more important impacts on the green FPAR than the proportion of PAV and optical properties of PAV. The significant relationships were found between spectral vegetation indices and the green FPAR, but EVI was more suitable to describe the variation of canopy green FPAR.

Energy minimization segmentation model based on MRI images.

Introduction: Medical image segmentation is an important tool for doctors to accurately analyze the volume of brain tissue and lesions, which is important for the correct diagnosis of brain diseases. However, manual image segmentation methods are time-consuming, subjective and lack of repeatability, it needs to develop automatic and reliable methods for image segmentation. Methods: Magnetic Resonance Imaging (MRI), a non-invasive imaging technique, is commonly used to detect, characterize and quantify tissues and lesions in the brain. Partial volume effect, gray scale in homogeneity, and lesions presents a great challenge for automatic medical image segmentation methods. So, the paper is dedicated to address the impact of partial volume effect and multiple sclerosis lesions on the segmentation accuracy in MRI. The objective function of the improved model and the post-processing method of lesion filling are researched based on the fuzzy clustering space and energy model. Results: In particular, an energy-minimized segmentation algorithm is proposed. Through experimental verification, the AR-FCM algorithm can better overcome the problem of low segmentation accuracy of the RFCM algorithm for tissue boundary voxels and improve the segmentation accuracy of this algorithm. Meanwhile, a multi-channel input energy-minimization segmentation method with lesion filling and anatomical mapping is further proposed. Discussion: The feasibility of the lesion filling strategy using post-processing can be confirmed and the segmentation accuracy is increased by comparison experiments.

A Ribosome-Related Prognostic Signature of Breast Cancer Subtypes Based on Changes in Breast Cancer Patients' Immunological Activity.

Background and Objectives. The prognostic role of adjacent nontumor tissue in patients with breast cancer (BC) is still unclear. The activity changes in immunologic and hallmark gene sets in normal tissues adjacent to BC may play a crucial role in predicting the prognosis of BC patients. The aim of this study was to identify BC subtypes and ribosome-associated prognostic genes based on activity changes of immunologic and hallmark gene sets in tumor and adjacent nontumor tissues to improve patient prognosis. Materials and Methods. Gene set variation analysis (GSVA) was applied to assess immunoreactivity changes in the overall sample and three immune-related BC subtypes were identified by non-negative matrix factorization (NMF). KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology) analyses were after determining the prognostic gene set using the least absolute shrinkage and selection operator (LASSO) method. Ribosome-related genes were identified by PPI (protein-protein interaction) analysis, and finally a prognostic risk model was constructed based on the expression of five ribosomal genes (RPS18, RPL11, PRLP1, RPL27A, and RPL38). Results. A comprehensive analysis of immune and marker genomic activity changes in normal breast tissue and BC tissue identified three immune-related BC subtypes. BC subtype 1 has the best prognosis, and subtype 3 has the worst overall survival rate. We identified a prognostic gene set in nontumor tissue by the least absolute shrinkage and selection operator (LASSO) method. We found that the results of both KEGG and GO analyses were indistinguishable from those of ribosome-associated genes. Finally, we determined that genes associated with ribosomes exhibit potential as a reliable predictor of overall survival in breast cancer patients. Conclusions. Our research provides an important guidance for the treatment of BC. After a mastectomy, the changes in gene set activity of both BC tissues and the nontumor tissues adjacent to it should be thoroughly evaluated, with special attention to changes in ribosome-related genes in the nontumor tissues.

Pharmaceutical targeting Th2-mediated immunity enhances immunotherapy response in breast cancer.

BACKGROUND: Breast cancer is a complex disease with a highly immunosuppressive tumor microenvironment, and has limited clinical response to immune checkpoint blockade (ICB) therapy. T-helper 2 (Th2) cells, an important component of the tumor microenvironment (TME), play an essential role in regulation of tumor immunity. However, the deep relationship between Th2-mediated immunity and immune evasion in breast cancer remains enigmatic. METHODS: Here, we first used bioinformatics analysis to explore the correlation between Th2 infiltration and immune landscape in breast cancer. Suplatast tosilate (IPD-1151 T, IPD), an inhibitor of Th2 function, was then employed to investigate the biological effects of Th2 blockade on tumor growth and immune microenvironment in immunocompetent murine breast cancer models. The tumor microenvironment was analyzed by flow cytometry, mass cytometry, and immunofluorescence staining. Furthermore, we examined the efficacy of IPD combination with ICB treatment by evaluating TME, tumor growth and mice survival. RESULTS: Our bioinformatics analysis suggested that higher infiltration of Th2 cells indicates a tumor immunosuppressive microenvironment in breast cancer. In three murine breast cancer models (EO771, 4T1 and EMT6), IPD significantly inhibited the IL-4 secretion by Th2 cells, promoted Th2 to Th1 switching, remodeled the immune landscape and inhibited tumor growth. Remarkably, CD8+ T cell infiltration and the cytotoxic activity of cytotoxic T lymphocyte (CTL) in tumor tissues were evidently enhanced after IPD treatment. Furthermore, increased effector CD4+ T cells and decreased myeloid-derived suppressor cells and M2-like macrophages were also demonstrated in IPD-treated tumors. Importantly, we found IPD reinforced the therapeutic response of ICB without increasing potential adverse effects. CONCLUSIONS: Our findings demonstrate that pharmaceutical inhibition of Th2 cell function improves ICB response via remodeling immune landscape of TME, which illustrates a promising combinatorial immunotherapy.

Cell image reconstruction using digital holography with an improved GS algorithm.

Digital holography is an effective technology in image reconstruction as amplitude and phase information of cells can be acquired without any staining. In this paper, we propose a holographic technique with an improved Gerchberg-Saxton (GS) algorithm to reconstruct cell imaging based on phase reconstruction information. Comparative experiments are conducted on four specific models to investigate the effectiveness of the proposed method. The morphological parameters (such as shape, volume, and sphericity) of abnormal erythrocytes can be obtained by reconstructing cell hologram of urinary sediment. Notably, abnormal red blood cells can also be detected in mussy circumstances by the proposed method, owing to the significantly biophysical contrast (refractive index distribution and mass density) between two different cells. Therefore, this proposed method has a broad application prospect in cell image reconstruction and cell dynamic detection.

Immune Profiling in Gastric Cancer Reveals the Dynamic Landscape of Immune Signature Underlying Tumor Progression.

The profiling of the tumor immune microenvironment (TIME) is critical for guiding immunotherapy strategies. However, how the composition of the immune landscape affects the tumor progression of gastric cancer (GC) is ill-defined. Here, we used mass cytometry to perform simultaneous in-depth immune profiling of the tumor, adjacent tissues, and blood cells from GC patients and revealed a unique GC tumor-immune signature, where CD8+ T cells were present at a lower frequency in tumor tissues compared to adjacent tissues, whereas regulatory T cells and tumor-associated macrophages (TAMs) were significantly increased, indicating strong suppressive TIME in GC. Incorporated with oncogenic genomic traits, we found that the unique immunophenotype was interactively shaped by a specific GC gene signature across tumor progression. Earlier-stage GC lesions with IFN signaling enrichment harbored significantly altered T-cell compartments while advanced GC featured by metabolism signaling activation was accumulated by TAMs. Interestingly, PD-1 expression on CD8+ T cells was relatively higher in earlier-stage GC patients, indicating that these patients may derive more benefits from PD-1 inhibitors. The dynamic properties of diverse immune cell types revealed by our study provide new dimensions to the immune landscape of GC and facilitate the development of novel immunotherapy strategies for GC patients.

FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts.

Background: Since T cell exclusion contributes to tumor immune evasion and immunotherapy resistance, how to improve T cell infiltration into solid tumors becomes an urgent challenge. Methods: We employed deep learning to profile the tumor immune microenvironment (TIME) in triple negative breast cancer (TNBC) samples from TCGA datasets and noticed that fibroblast growth factor receptor (FGFR) signaling pathways were enriched in the immune-excluded phenotype of TNBC. Erdafitinib, a selective FGFR inhibitor, was then used to investigate the effect of FGFR blockade on TIME landscape of TNBC syngeneic mouse models by flow cytometry, mass cytometry (CyTOF) and RNA sequencing. Cell Counting Kit-8 (CCK-8) assay and transwell migration assay were carried out to detect the effect of FGFR blockade on cell proliferation and migration, respectively. Cytokine array, western blot, enzyme-linked immunosorbent assay (ELISA) and immunofluorescence (IF) were employed to investigate the potential mechanism by which FGFR inhibition enhanced T cell infiltration. Results: Blocking FGFR pathway by Erdafitinib markedly suppressed tumor growth with increased T cell infiltration in immunocompetent mouse models of TNBC. Mechanistically, FGFR blockade inhibited cancer-associated fibroblasts (CAFs) proliferation, migration and secretion of vascular cell adhesion molecule 1 (VCAM-1) by down-regulating MAPK/ERK pathway in CAFs, thus promoting T cell infiltration by breaking physical and chemical barriers built by CAFs in TIME. Furthermore, we observed that FGFR inhibition combined with immune checkpoint blockade therapy (ICT) greatly improved the therapeutic response of TNBC tumor models. Conclusions: FGFR blockade enhanced ICT response by turning immune "cold" tumor into "hot" tumor, providing remarkable implications of FGFR inhibitors as adjuvant agents for combinatorial immunotherapy.

Targeting breast cancer with a combination of DNT and LAG3 checkpoint blockage and its mechanism.

INTRODUCTION: The characteristics of the tumor immune microenvironment (TIME) are closely related to immunotherapy. Breast cancer can benefit from immunotherapy, and its TIME is still unclear. METHODS: We utilized mass cytometry to explore the immune cell heterogeneity in breast cancer. Double-negative T cells (DNTs) from healthy volunteers (HBs) were enriched in vitro. Flow cytometry was used to detect the cell surface receptors of cancer cells and DNT cells. The correlation between immune checkpoints and the abundance of immune cells or prognosis of breast cancer was analyzed by the TCGA database. The messenger RNA (mRNA) expression of functional genes was performed by quantitative real-time PCR. RESULTS: We found that the frequencies of Granzyme B (GZMB)+ CD8+ T and GZMB+ DNT cells in cancer tissues (CA) of breast cancer were lower than those in blood samples of patients (PB), and the frequencies of programmed cell death protein 1 (PD1)+ CD8+ T and PD1+ DNT cells in CA were higher than those in PB. DNTs from HBs had a cytotoxic effect on MDA-MB-231. LAG3Ab could upregulate the mRNA expression of interferon gamma and perforin by increasing T-BET transcription to enhance the cytotoxicity of DNT cells in vitro. CONCLUSION: Our study revealed the suppressive status of TIME in breast cancer and supported DNT cells had the potential to be applied as a novel adoptive cell therapy for TNBC either alone or combined with LAG3Ab.

Gut microbiota influence immunotherapy responses: mechanisms and therapeutic strategies.

The gut microbiota have long been recognized to play a key role in human health and disease. Currently, several lines of evidence from preclinical to clinical research have gradually established that the gut microbiota can modulate antitumor immunity and affect the efficacy of cancer immunotherapies, especially immune checkpoint inhibitors (ICIs). Deciphering the underlying mechanisms reveals that the gut microbiota reprogram the immunity of the tumor microenvironment (TME) by engaging innate and/or adaptive immune cells. Notably, one of the primary modes by which the gut microbiota modulate antitumor immunity is by means of metabolites, which are small molecules that could spread from their initial location of the gut and impact local and systemic antitumor immune response to promote ICI efficiency. Mechanistic exploration provides novel insights for developing rational microbiota-based therapeutic strategies by manipulating gut microbiota, such as fecal microbiota transplantation (FMT), probiotics, engineered microbiomes, and specific microbial metabolites, to augment the efficacy of ICI and advance the age utilization of microbiota precision medicine.

Vitamin E Enhances Cancer Immunotherapy by Reinvigorating Dendritic Cells via Targeting Checkpoint SHP1.

Despite the popular use of dietary supplements during conventional cancer treatments, their impacts on the efficacies of prevalent immunotherapies, including immune-checkpoint therapy (ICT), are unknown. Surprisingly, our analyses of electronic health records revealed that ICT-treated patients with cancer who took vitamin E (VitE) had significantly improved survival. In mouse models, VitE increased ICT antitumor efficacy, which depended on dendritic cells (DC). VitE entered DCs via the SCARB1 receptor and restored tumor-associated DC functionality by directly binding to and inhibiting protein tyrosine phosphatase SHP1, a DC-intrinsic checkpoint. SHP1 inhibition, genetically or by VitE treatment, enhanced tumor antigen cross-presentation by DCs and DC-derived extracellular vesicles (DC-EV), triggering systemic antigen-specific T-cell antitumor immunity. Combining VitE with DC-recruiting cancer vaccines or immunogenic chemotherapies greatly boosted ICT efficacy in animals. Therefore, combining VitE supplement or SHP1-inhibited DCs/DC-EVs with DC-enrichment therapies could substantially augment T-cell antitumor immunity and enhance the efficacy of cancer immunotherapies. SIGNIFICANCE: The impacts of nutritional supplements on responses to immunotherapies remain unexplored. Our study revealed that dietary vitamin E binds to and inhibits DC checkpoint SHP1 to increase antigen presentation, prime antitumor T-cell immunity, and enhance immunotherapy efficacy. VitE-treated or SHP1-silenced DCs/DC-EVs could be developed as potent immunotherapies. This article is highlighted in the In This Issue feature, p. 1599.

The allergy mediator histamine confers resistance to immunotherapy in cancer patients via activation of the macrophage histamine receptor H1.

Reinvigoration of antitumor immunity remains an unmet challenge. Our retrospective analyses revealed that cancer patients who took antihistamines during immunotherapy treatment had significantly improved survival. We uncovered that histamine and histamine receptor H1 (HRH1) are frequently increased in the tumor microenvironment and induce T cell dysfunction. Mechanistically, HRH1-activated macrophages polarize toward an M2-like immunosuppressive phenotype with increased expression of the immune checkpoint VISTA, rendering T cells dysfunctional. HRH1 knockout or antihistamine treatment reverted macrophage immunosuppression, revitalized T cell cytotoxic function, and restored immunotherapy response. Allergy, via the histamine-HRH1 axis, facilitated tumor growth and induced immunotherapy resistance in mice and humans. Importantly, cancer patients with low plasma histamine levels had a more than tripled objective response rate to anti-PD-1 treatment compared with patients with high plasma histamine. Altogether, pre-existing allergy or high histamine levels in cancer patients can dampen immunotherapy responses and warrant prospectively exploring antihistamines as adjuvant agents for combinatorial immunotherapy.

AMPD1 Is Associated With the Immune Response and Serves as a Prognostic Marker in HER2-Positive Breast Cancer.

BACKGROUND: Although immunotherapy has been used in the treatment of metastatic triple negative breast cancer (TNBC), its therapeutic influence on human epidermal growth factor receptor 2 (HER2)-positive subtype remains controversial. It is therefore imperative to find biomarkers that can predict the immune response in HER2+ BC. METHODS: ESTIMATE was utilized to compute the ImmuneScore and StromalScore from data obtained from TCGA database, and differentially expressed genes (DEGs) were identified. In addition, univariate Cox regression was used to assess candidate genes such as AMPD1, CD33, and CCR5. Gene set enrichment analysis (GSEA) was used to further understand AMPD1-associated pathways. Moreover, immunohistochemical analyses were performed to further reveal the relationship among AMPD1, CD4 and CD8 genes. RESULTS: The expression of AMPD1 was markedly associated with disease outcome and tumor-infiltrating immune cells (TICs). In addition, AMPD1 was associated with lymph node status, age and the expression of PD-L1 and PD-L2. High AMPD1 expression was linked to longer overall survival (OS). Upregulated expression of AMPD1 correlated with the enrichment of immune-related signaling pathways. In addition, immunohistochemical analyses demonstrated a co-expression profile among AMPD1, CD4 and CD8 genes. CONCLUSIONS: Taken together, our data demonstrated that AMPD1 might serve as a novel biomarker for predicting the immune response and disease outcome in HER2+ BC.

An advanced BiPO4/super P anode material for high-performance potassium-ion batteries.

Dispersed BiPO4 nanoparticles loaded on the surface of a super P conducting network (BiPO4/SP) were fabricated and investigated as a novel anode for PIBs. The BiPO4/SP electrode demonstrates high rate capability (97.1 mA h g-1 at 500 mA g-1) and good long-term cycling performance (116 mA h g-1 at 200 mA g-1 over 100 cycles).

Multi-Omics Analysis of the Anti-tumor Synergistic Mechanism and Potential Application of Immune Checkpoint Blockade Combined With Lenvatinib.

The combination of immune-checkpoint blockade (ICB) and lenvatinib has demonstrated robust clinical effects that are superior to those of monotherapies, but the synergistic anti-tumor mechanisms remain unclear. Exploring the synergistic molecular mechanisms and early identifying potential application have key importance for clinical therapeutics. We firstly systematically reviewed published data of ICB in combination with lenvatinib for the treatment of cancer by meta-analysis. A subsequent bioinformatics analysis explored the mechanism of combined ICB and lenvatinib therapy in 33 cancer types. Transcriptomic analysis was conducted by RNA-seq, and genomic analysis was performed on gene mutations and copy-number alteration data. Tumor-related pathways and tumor immune micro-environment (TIME) were also investigated. The meta-analysis showed a 38.0% objective response rate (ORR) and 79% disease control rate (DCR) for ICB combined with lenvatinib. Multi-omics analysis revealed that ICB and lenvatinib target genes were highly expressed and showed driving alterations in six specific malignancies. Pathway-enrichment analysis found target genes were implicated in tumor development, angiogenesis, and immunoregulatory associated pathways. This study verified the potential synergistic mechanisms of ICB combined with lenvatinib at transcriptomics, genomics, protein, and cellular levels and recognized nine tumor types had ≥ 2 positive treatment-related molecular characteristics, which might benefit particularly from this combined strategy. The findings would help to provide clinical insights and theoretical basis for optimizing of targeted therapy-immunotherapy combinations, and for guiding individualized precision-medicine approaches for cancer treatment.

Breast-Conserving Therapy Has Better Prognosis for Tumors in the Central and Nipple Portion of Breast Cancer Compared with Mastectomy: A SEER Data-Based Study.

BACKGROUND AND OBJECTIVES: Currently, the location of primary tumor was an independent prognostic factor of breast cancer. Tumors in the central and nipple portion (TCNP) had poor prognosis compared to other peripheral quadrants. The breast-conserving therapy (BCT) is becoming increasingly common worldwide in breast cancer operations. However, whether the availability of BCT was performed for TCNP remained a matter of debate. We sought to investigate whether BCT was suitable for TCNP with respect to survival outcomes, compared with mastectomy therapy. METHODS: Utilizing the Surveillance, Epidemiology, and End Results (SEER) database, we obtained TCNP breast cancer patients diagnosed during the period of 2010-2015. One-to-one (1:1) propensity score matching (PSM) was applied to construct a matched sample consisting of pairs of BCT and mastectomy groups. Univariate and multivariate Cox proportional hazard models were applied to estimate the factors associated with breast cancer-specific survival (BCSS) and overall survival (OS). Survival analysis was performed with the Kaplan-Meier method. RESULTS: In the overall cohort, a total of 9,900 patients were enrolled. We found that patients with BCT showed significantly better BCSS (log-rank, p < 0.001) and OS (log-rank, p < 0.001) than the mastectomy group before PSM. The same finding was also shown in 5,820 patients after PSM. Additionally, none of the subgroups, including age, sex, race, histological grade, AJCC stage, and molecular subtype undergoing mastectomy therapy, had better BCSS than BCT. CONCLUSIONS: Our study was the first research to show that BCT exhibited superior prognosis in the cohort of TCNP from SEER databases than mastectomy therapy. This finding could provide a cue for treatment strategies for suitable TCNP patients, especially those with a strong willingness to conserve their breasts.