18 Sep 2024·Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico

Construction and clinical significance of prognostic risk markers based on cancer driver genes in lung adenocarcinoma.

Article

Author: Li, Jingyan ; Huo, Tingting ; Su, Yazhou ; Wang, Yanan

BACKGROUNDCancer driver genes (CDGs) have been reported as key factors influencing the progression of lung adenocarcinoma (LUAD). However, the role of CDGs in LUAD prognosis has not been fully elucidated.METHODSLUAD transcriptome data and CDG-related data were obtained from public databases and literature. Differentially expressed CDGs (DE-CDGs) greatly associated with LUAD survival (P < 0.05) were identified to establish a prognostic model. In addition, immune analysis of high-risk (HR) and low-risk (LR) groups was conducted by utilizing the CIBERSORT and single sample gene set enrichment analysis (ssGSEA) algorithms to assess immune differences. Subsequently, mutation analysis was conducted using maftools. Finally, candidate drugs were identified using the CellMiner database.RESULTS40 DE-CDGs significantly associated with LUAD survival and 11 DE-CDGs associated with prognosis were identified through screening. Regression analysis revealed that risk score can independently predict LUAD prognosis (P < 0.05). Immune landscape analysis revealed that compared to the HR group, the LR group had higher immune scores and high infiltration of various immune cells such as follicular helper B cells and T cells. Mutation landscape analysis demonstrated that missense mutation was the most common mutation type in both risk groups. Drug prediction analysis revealed strong correlations of fulvestrant, S-63845, sapacitabine, lomustine, BLU-667, SR16157, motesanib, AZD-9496, XK-469, dimethylfasudil, P-529, and imatinib with the model genes, suggesting their potential as candidate drugs targeting the model genes.CONCLUSIONThis study identified 11 effective biomarkers, DE-CDGs, which can predict LUAD prognosis and explored the biological significance of CDGs in LUAD prognosis, immunotherapy, and treatment.

01 Aug 2024·Biotechnology and Applied Biochemistry

Development of a prognostic model for lung adenocarcinoma polarity‐related genes and analysis of immune landscape

Article

Author: Du, Wenqiang ; Xu, Hongqiu ; Jing, Xuelong ; Li, Pengfei ; Xie, Jingen

AbstractDespite the progress made in the management of lung adenocarcinoma (LUAD), the overall prognosis for LUAD individuals remains suboptimal. While the role of cell polarity in tumor invasion and metastasis is well established, its prognostic significance in LUAD is still unknown. Differential analysis was performed on the Cancer Genome Atlas (TCGA)‐LUAD and normal lung tissue, and candidate genes were identified by intersecting differentially expressed genes with polarity‐related genes (PRGs). A prognostic model was constructed using univariate and multivariate Cox regression and LASSO regression. To enhance the robustness of the analysis, an independent prognostic analysis was conducted by incorporating relevant clinical information. The accuracy and sensitivity of the model were validated using survival analysis and ROC curves. Finally, immune landscape, immune therapy, tumor mutation burden, and drug sensitivity analysis were carried out on high‐ and low‐risk patients. Ten prognostic genes were screened to divide LUAD patients into different risk groups. Survival analysis, ROC curves, and univariate/multivariate Cox regression analyses collectively demonstrated the favorable predictive performance of the model, which could be an independent prognostic factor. The nomogram, in conjunction with the calibration curve, demonstrated the model's compelling predictive capacity in prognosticating the overall survival of LUAD individuals. Low‐risk LUAD patients exhibited heightened levels of immune cell infiltration, immune scores, and immune checkpoint expression compared to high‐risk individuals. So, they may have a greater likelihood of benefiting from immune therapy. The high‐risk group demonstrated a remarkably higher tumor mutation burden (TMB) in contrast with the low‐risk group. XAV‐939, Fulvestrant, and SR16157 may have potential value in the clinical use of LUAD. We revealed the potential linkage between PRGs and LUAD prognosis, and the application of these prognostic factors in risk stratification and prognosis prediction of LUAD patients may be of great significance.

01 Sep 2013·The Journal of Steroid Biochemistry and Molecular BiologyQ2 · BIOLOGY

Current status on development of steroids as anticancer agents

Q2 · BIOLOGY

Review

Author: B. Sathish Kumar ; Atul Gupta ; Arvind S. Negi

Steroids are important biodynamic agents. Their affinities for various nuclear receptors have been an interesting feature to utilize them for drug development particularly for receptor mediated diseases. Steroid biochemistry and its crucial role in human physiology, has attained importance among the researchers. Recent years have seen an extensive focus on modification of steroids. The rational modifications of perhydrocyclopentanophenanthrene nucleus of steroids have yielded several important anticancer lead molecules. Exemestane, SR16157, fulvestrant and 2-methoxyestradiol are some of the successful leads emerged on steroidal pharmacophores. The present review is an update on some of the steroidal leads obtained during past 25 years. Various steroid based enzyme inhibitors, antiestrogens, cytotoxic conjugates and steroidal cytotoxic molecules of natural as well as synthetic origin have been highlighted. This article is part of a Special Issue entitled "Synthesis and biological testing of steroid derivatives as inhibitors".

100 Deals associated with HLX-801

R&D Status

10 top R&D records.

to view more data

Indication	Highest Phase	Country/Location	Organization	Date
Breast Cancer	Phase 2	-	Helix Therapeutics, Inc.	-

Clinical Result

Indication

Phase

Evaluation

View All Results

Translational Medicine

Boost your research with our translational medicine data.

view full example data

Deal

Boost your decision using our deal data.

view full example data

Core Patent

Boost your research with our Core Patent data.

view full example data

Clinical Trial

Identify the latest clinical trials across global registries.

view full example data

Approval

Accelerate your research with the latest regulatory approval information.

view full example data

Regulation

Understand key drug designations in just a few clicks with Synapse.

view full example data

Chat with Hiro

Get started for free today!

Accelerate Strategic R&D decision making with Synapse, PatSnap’s AI-powered Connected Innovation Intelligence Platform Built for Life Sciences Professionals.

Start your data trial now!

Synapse data is also accessible to external entities via APIs or data packages. Empower better decisions with the latest in pharmaceutical intelligence.

Bio

Bio Sequences Search & Analysis

Chemical

Chemical Structures Search & Analysis


No Data

HLX-801

Overview

Basic Info

Structure

Related

R&D Status

Clinical Result

Translational Medicine

Deal

Core Patent

Clinical Trial

Approval

Regulation