CDKL3 shapes immunosuppressive tumor microenvironment and initiates autophagy in esophageal cancer.

Background: CDKL3 has been associated with the prognosis of several tumors. However, the potential role of CDKL3 in immunotherapy and the tumor microenvironment (TME) in esophageal carcinoma (ESCA) remains unclear. Methods: In this study, Cox regression analysis was used to assess the predictive value of CDKL3 for ESCA outcomes. We systematically correlated CDKL3 with immunological features in the TME. The role of CDKL3 in predicting the efficacy of immunotherapy was also analyzed. Correlation analysis, Cox analysis and LASSO Cox regression were used to construct the CDKL3-related autophagy (CrA) risk score model. The relationship between CDKL3 expression and postoperative pathological complete response (pCR) rate in esophageal squamous cell carcinoma (ESCC) patients undergoing neoadjuvant chemoradiotherapy (nCRT) was evaluated using Immunohistochemical staining (IHC). The relationship between CDKL3 expression and autophagy induction was confirmed by immunofluorescence staining and western blot, and the effect of CDKL3 expression on macrophage polarization was verified by flow cytometry. Results: High expression of CDKL3 was found in ESCA and was associated with poor prognosis in ESCA. Moreover, CDKL3 expression was negatively correlated with tumor-infiltrating immune cells (TIICs), the integrality of the cancer immunity cycles, and anti-tumor signatures, while CDKL3 expression was positively correlated with suppressive TME-related chemokines and receptors, immune hyperprogressive genes, and suppressive immune checkpoint, resulting in immunosuppressive TME formation in ESCA. An analysis of immunotherapy cohorts of the ESCA and pan-cancer showed a better response to immunotherapy in tumor patients with lower CDKL3 levels. The CrA risk score model was constructed and validated to accurately predict the prognosis of ESCA. Notably, the CrA risk score of ESCA patients was significantly positively correlated with M2 macrophages. Furthermore, knockdown CDKL3 in KYSE150 cells could inhibit autophagy induction and M2 macrophage polarization. And, radiation could downregulate CDKL3 expression and autophagy induction, while ESCC patients with high CDKL3 expression had a significantly lower response rate after nCRT than those with low CDKL3 expression. Conclusion: CDKL3 may play an important role in anti-tumor immunity by regulating autophagy to promote the formation of immunosuppressive TME, thus playing a critical role in the prognosis of ESCA.

Multi-omics Mendelian randomization integrating GWAS, eQTL, and mQTL data identified genes associated with breast cancer.

Breast cancer (BC) remains a major disease posing a threat to women's health, but the underlying biological interpretation remains largely unknown. Here, we aimed to identify genes associated with breast cancer and analyze their pathophysiological mechanisms based on multi-omics Mendelian randomization (MR). Summary-data-based MR (SMR) was performed to estimate the causal effects of blood and breast mammary tissue expression quantitative trait loci (eQTLs) on BC. External validation analysis was used to validate the identified genes. Integration analyses BC GWAS summaries with eQTLs and DNA methylation QTLs (mQTLs) from the blood were conducted using SMR to prioritize putative blood genes and their regulatory elements associated with BC risk. Finally, two prior genes (ATG10 and RCCD1) from blood tissue reached significant levels in both BCAC (ATG10: ORBRCR = 0.91, PBRCR = 1.29 × 10-11; RCCD1: ORBRCR = 0.90, PBRCR = 3.72 × 10-15) and FinnGen cohorts (ATG10: ORFinnGen = 0.89, PFinnGen = 8.55 × 10-5; RCCD1: ORFinnGen = 0.89, PFinnGen = 2.38 × 10-8). Additionally, those two genes from breast tissues also replicated in both BCAC (ATG10: ORBRCR = 0.95, PBRCR = 1.02 × 10-9; RCCD1: ORBRCR = 0.87, PBRCR = 4.70 × 10-10) and FinnGen cohorts (ATG10: ORFinnGen = 0.93, PFinnGen = 2.38 × 10-4; RCCD1: ORFinnGen = 0.85, PFinnGen = 3.81 × 10-6). Sensitive analysis and external validation analysis validated those two identified genes. Multi-omics MR analysis showed that the SNP signals associated with ATG10 and RCCD1 were significant across the data from BC Genome-wide association study (GWAS), eQTL, and mQTL studies. In conclusion, we identified two priority genes that are potentially associated with BC. These findings improve our limited understanding of the mechanism of BC and shed light on the development of therapeutic agents for treating BC.

Lactylation-related gene signature for prognostic prediction and immune infiltration analysis in breast cancer.

Background: Lactylation is implicated in various aspects of tumor biology, but its relation to breast cancer remains poorly understood. This study aimed to explore the roles of the lactylation-related genes in breast cancer and its association with the tumor microenvironment. Methods: The expression and mutation patterns of lactylation-related genes were analyzed using the breast cancer data from The Cancer Genome Atlas (TCGA) database and GSE20685 datasets. Unsupervised clustering was used to identify two lactylation clusters. A lactylation-related gene signature was developed and validated using the training and validation cohorts. Immune cell infiltration and drug response were assessed. Results: We analyzed the mRNA expression, copy number variations, somatic mutations, and correlation networks of 22 lactylation-related genes in breast cancer tissues. We identified two distinct lactylation clusters with different survival outcomes and immune microenvironments. We further classified the patients into two gene subtypes based on lactylation clusters and identified a 7-gene signature for breast cancer survival prognosis. The prognostic score based on this signature demonstrated prognostic value and predicted the therapeutic response. Conclusion: Lactylation-related genes play a critical role in breast cancer by influencing tumor growth, immune microenvironment, and drug response. This lactylation-related gene signature may serve as a prognostic marker and a potential therapeutic target for breast cancer.

Effect of genetic liability to migraine and its subtypes on breast cancer: a mendelian randomization study.

BACKGROUND: The relationship between migraine and breast cancer risk has generated conflicting findings. We attempted to assess the association between migraine and breast cancer risk using Mendelian randomization (MR) analysis. METHODS: We selected genetic instruments associated with migraine from a recently published genome-wide association studies (GWAS). Inverse variant weighted (IVW) analysis was adopted as the main method, and we also performed the weighted-median method and the MR‒Egger, MR pleiotropy residual sum and outlier (MR-PRESSO), and MR Robust Adjusted Profile Score (MR-RAPS) methods as supplements. RESULTS: Our MR suggested that any migraine (AM) was a risk factor for overall breast cancer (IVW: odds ratio (OR) = 1.072, 95% confidence intervals (CI) = 1.035-1.110, P = 8.78 × 10- 5, false discovery rate (FDR) = 7.36 × 10- 4) and estrogen receptor-positive (ER+) breast cancer (IVW: OR = 1.066, 95% CI = 1.023-1.111, P = 0.0024; FDR = 0.0108) but not estrogen receptor-negative (ER-) breast cancer. In its subtype analysis, women with a history of migraine without aura (MO) had an increased risk of ER- breast cancer (IVW: OR = 1.089, 95% CI = 1.019-1.163, P = 0.0118, FDR = 0.0354), and MO was suggestively associated with the risk of overall breast cancer (FDR > 0.05 and IVW P < 0.05). No significant heterogeneity or horizontal pleiotropy was found in the sensitivity analysis. CONCLUSION: This study suggested that women with AM have an increased risk of overall breast cancer and ER + breast cancer. MO was suggestively associated with the risk of overall breast cancer and ER- breast cancer.

A bibliometric analysis of metastatic breast cancer: two-decade report (2002-2022).

Background: MBC is a lethal form of breast cancer that arises when cancer cells invade other organs or tissues. The treatment of MBC needs personalized approaches based on the tumor and patient characteristics. The purpose of this paper is to analyze MBC studies from 2002 to 2022 using bibliometrics and to investigate its current situation, main contributors, core journals, highly cited papers, and topic evolution. Materials and methods: We retrieved data from Web of Science Core Collection (WOSCC). Bibliometric analysis of the included literatures mainly used the following tools: the function of "analyze results" and "citation report" in WoS, Microsoft excel 2021, CiteSpace v.6.1. R6, VOSviewer v.1.6.18, BICOMB v.2.04 and gCLUTO v.1.0. Results: We found 12,653 articles on MBC research published in 1, 802 journals by 69, 753 authors from 118 countries. The annual output and citation of MBC articles showed a rising trend over time. The United States was the most influential country in MBC research. The most cited journal in this field was The Journal of Clinical Oncology. And the most cited article was by Slamon DJ. The co-word analysis of keywords divides MBC into six research clusters. The hormone receptor-positive MBC and liquid biopsy of MBC are the frontiers research trends. "CDK4/6 inhibitor" had the highest burst strength. Conclusion: Our bibliometric analysis offers a comprehensive overview of MBC research in the past two decades. It shows the current situation, main contributors, core journals, highly cited papers, and topic evolution of this field. Our study can assist researchers and practitioners to comprehend the development and trends of MBC research and to discover potential directions for future research.

Authentication of a survival nomogram for non-invasive micropapillary breast cancer.

Purpose: We aimed at establishing a nomogram to accurately predict the overall survival (OS) of non-metastatic invasive micropapillary breast carcinoma (IMPC). Methods: In the training cohort, data from 429 patients with non-metastatic IMPC were obtained through the Surveillance, Epidemiology, and End Results (SEER) database. Other 102 patients were enrolled at the Xijing Hospital as validation cohort. Independent risk factors affecting OS were ascertained using univariate and multivariate Cox regression. A nomogram was established to predict OS at 3, 5 and 8 years. The concordance index (C-index), the area under a receiver operating characteristic (ROC) curve and calibration curves were utilized to assess calibration, discrimination and predictive accuracy. Finally, the nomogram was utilized to stratify the risk. The OS between groups was compared through Kaplan-Meier survival curves. Results: The multivariate analyses revealed that race (p = 0.047), surgery (p = 0.003), positive lymph nodes (p = 0.027), T stage (p = 0.045) and estrogen receptors (p = 0.019) were independent prognostic risk factors. The C-index was 0.766 (95% CI, 0.682-0.850) in the training cohort and 0.694 (95% CI, 0.527-0.861) in the validation cohort. Furthermore, the predicted OS was consistent with actual observation. The AUCs for OS at 3, 5 and 8 years were 0.786 (95% CI: 0.656-0.916), 0.791 (95% CI: 0.669-0.912), and 0.774 (95% CI: 0.688-0.860) in the training cohort, respectively. The area under the curves (AUCs) for OS at 3, 5 and 8 years were 0.653 (95% CI: 0.498-0.808), 0.683 (95% CI: 0.546-0.820), and 0.716 (95% CI: 0.595-0.836) in the validation cohort, respectively. The Kaplan-Meier survival curves revealed a significant different OS between groups in both cohorts (p<0.001). Conclusion: Our novel prognostic nomogram for non-metastatic IMPC patients achieved a good level of accuracy in both cohorts and could be used to optimize the treatment based on the individual risk factors.

Icariin Induces Triple-Negative Breast Cancer Cell Apoptosis and Suppresses Invasion by Inhibiting the JNK/c-Jun Signaling Pathway.

Background: Breast cancer is a common cancer worldwide. Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer characterized by a poor prognosis. Icariin (ICA) is a flavonoid glycoside purified from the natural product Epimedium, which is reported to exert an inhibitory effect on a variety of cancers. However, molecular mechanisms behind ICA suppressed TNBC remain elusive. Methods: The curative effects of ICA on TNBC cells and potential targets were predicted by network pharmacology and molecular biology methods screening, and the mechanism of inhibition was explained through in vitro experiments such as cell function determination, Western blot analysis, molecular docking verification, etc. Results: This study showed that ICA inhibits TNBC cell functions such as proliferation, migration, and invasion in a dose-dependent manner. ICA could induce redox-induced apoptosis in TNBC cell, as shown by ROS upregulation. As a result of network pharmacology, ICA was predicted to be able to inhibit the MAPK signaling pathway. ICA treatment inhibited the expression of JNK and c-Jun and downregulated the antiapoptotic gene cIAP-2. Our results suggested that ICA could induce apoptosis by inducing an excessive accumulation of ROS in cells and suppress TNBC cell invasion via the JNK/c-Jun signaling pathway. Conclusion: We demonstrated that ICA can effectively inhibit cell proliferation and induced apoptosis of TNBC cells. In addition, ICA could inhibit TNBC cell invasion through the JNK/c-Jun signaling pathway. The above suggests that ICA may become a potential drug for TNBC.