Differential expression analysis of JAK/STAT pathway related genes in breast cancer

Role of STAT3 in the initiation, progression, proliferation and metastasis of breast cancer and strategies to deliver JAK and STAT3 inhibitors

INTRODUCTION

Breast cancer (BC) accounts for the majority of cancers among the female population. Anomalous activation of various signaling pathways has become an issue of concern. The JAK-STAT signaling pathway is activated in numerous cancers, including BC. STAT3 is widely involved in BCs, as 40 % of BCs display phosphorylated STAT3. JAK-STAT signaling is crucial for proliferation, survival, metastasis and other cellular events associated with the tumor microenvironment. Hence, targeting this pathway has become an area of interest among researchers.

KEY FINDINGS

This review article focuses on the role of STAT3 in the initiation, proliferation, progression and metastasis of BC. The roles of various phytochemicals, synthetic molecules and biologicals against JAK-STAT and STAT3 in various cancers have been discussed, with special emphasis on BC.

SIGNIFICANCE

JAK and STAT3 are involved in various phases from initiation to metastasis, and targeting this pathway is a promising approach to inhibit the various stages of BC development and to prevent metastasis. A number of phytochemicals and synthetic and biological molecules have demonstrated potential inhibitory effects on JAK and STAT3, thereby paving the way for the development of better therapeutics against BC.

Targeting Streptomyces-Derived Streptenol Derivatives against Gynecological Cancer Target PIK3CA: An In Silico Approach

Streptomyces is amongst the most amenable genera for biotechnological applications, and it is extensively used as a scaffold for drug development. One of the most effective therapeutic applications in the treatment of cancer is targeted therapy. Small molecule therapy is one of them, and it has gotten a lot of attention recently. Streptomyces derived compounds namely streptenols A, C, and F-I and streptazolin were subjected for ADMET property assessment. Our computational studies based on molecular docking effectively displayed the synergistic effect of streptomyces-derived compounds on the gynecological cancer target PIK3CA. These compounds were observed with the highest docking scores as well as promising intermolecular interaction stability throughout the molecular dynamic simulation. Molecular docking and molecular dynamic modeling techniques were utilized to investigate the binding mode stability of drugs using a pharmacophore scaffold, as well as physicochemical and pharmacokinetic aspects linked to alpelisib. With a root mean square fluctuation of the protein backbone of less than 0.7 nm, they demonstrated a steady binding mode in the target binding pocket. They have also prompted hydrogen bonding throughout the simulations, implying that the chemicals have firmly occupied the active site. A comprehensive study showed that streptenol D, streptenol E, streptenol C, streptenol G, streptenol F, and streptenol B can be considered as lead compounds for PIK3CA-based inhibitor design. To warrant the treatment efficacy against cancer, comprehensive computational research based on proposed chemicals must be assessed through in vitro studies.

TYK2: An Upstream Kinase of STATs in Cancer

In this review we concentrate on the recent findings describing the oncogenic potential of the protein tyrosine kinase 2 (TYK2). The overview on the current understanding of TYK2 functions in cytokine responses and carcinogenesis focusses on the activation of the signal transducers and activators of transcription (STAT) 3 and 5. Insight gained from loss-of-function (LOF) gene-modified mice and human patients homozygous for Tyk2/TYK2-mutated alleles established the central role in immunological and inflammatory responses. For the description of physiological TYK2 structure/function relationships in cytokine signaling and of overarching molecular and pathologic properties in carcinogenesis, we mainly refer to the most recent reviews. Dysregulated TYK2 activation, aberrant TYK2 protein levels, and gain-of-function (GOF) TYK2 mutations are found in various cancers. We discuss the molecular consequences thereof and briefly describe the molecular means to counteract TYK2 activity under (patho-)physiological conditions by cellular effectors and by pharmacological intervention. For the role of TYK2 in tumor immune-surveillance we refer to the recent Special Issue of Cancers "JAK-STAT Signaling Pathway in Cancer".

Identification of an eight-lncRNA prognostic model for breast cancer using WGCNA network analysis and a Cox‑proportional hazards model based on L1-penalized estimation

An ever‑increasing number of long noncoding (lnc)RNAs has been identified in breast cancer. The present study aimed to establish an lncRNA signature for predicting survival in breast cancer. RNA expression profiling was performed using microarray gene expression data from the National Center for Biotechnology Information Gene Expression Omnibus, followed by the identification of breast cancer‑related preserved modules using weighted gene co‑expression network (WGCNA) network analysis. From the lncRNAs identified in these preserved modules, prognostic lncRNAs were selected using univariate Cox regression analysis in combination with the L1‑penalized (LASSO) Cox‑proportional Hazards (Cox‑PH) model. A risk score based on these prognostic lncRNAs was calculated and used for risk stratification. Differentially expressed RNAs (DERs) in breast cancer were identified using MetaDE. Gene Set Enrichment Analysis pathway enrichment analysis was conducted for these prognostic lncRNAs and the DERs related to the lncRNAs in the preserved modules. A total of five preserved modules comprising 73 lncRNAs were mined. An eight‑lncRNA signature (IGHA1, IGHGP, IGKV2‑28, IGLL3P, IGLV3‑10, AZGP1P1, LINC00472 and SLC16A6P1) was identified using the LASSO Cox‑PH model. Risk score based on these eight lncRNAs could classify breast cancer patients into two groups with significantly different survival times. The eight‑lncRNA signature was validated using three independent cohorts. These prognostic lncRNAs were significantly associated with the cell adhesion molecules pathway, JAK‑signal transducer and activator of transcription 5A pathway, and erbb pathway and are potentially involved in regulating angiotensin II receptor type 1, neuropeptide Y receptor Y1, KISS1 receptor, and C‑C motif chemokine ligand 5. The developed eight‑lncRNA signature may have clinical implications for predicting prognosis in breast cancer. Overall, this study provided possible molecular targets for the development of novel therapies against breast cancer.