Artificial intelligence (AI) is a branch of computer science that includes research in robotics, language recognition, image recognition, natural language processing, and expert systems. AI is poised to change medical practice, and oncology is not an exception to this trend. As the matter of fact, lung cancer has the highest morbidity and mortality worldwide. The leading cause is the complexity of associating early pulmonary nodules with neoplastic changes and numerous factors leading to strenuous treatment choice and poor prognosis. AI can effectively enhance the diagnostic efficiency of lung cancer while providing optimal treatment and evaluating prognosis, thereby reducing mortality. This review seeks to provide an overview of AI relevant to all the fields of lung cancer. We define the core concepts of AI and cover the basics of the functioning of natural language processing, image recognition, human-computer interaction and machine learning. We also discuss the most recent breakthroughs in AI technologies and their clinical application regarding diagnosis, treatment, and prognosis in lung cancer. Finally, we highlight the future challenges of AI in lung cancer and its impact on medical practice.

The E2F family of transcription factors (E2Fs) consist of eight genes in mammals. These genes encode ten proteins that are usually classified as transcriptional activators or transcriptional repressors. E2Fs are important for many cellular processes, from their canonical role in cell cycle regulation to other roles in angiogenesis, the DNA damage response and apoptosis. A growing body of evidence demonstrates that cancer stem cells (CSCs) are key players in tumor development, metastasis, drug resistance and recurrence. This review focuses on the role of E2Fs in CSCs and notes that many signals can regulate the activities of E2Fs, which in turn can transcriptionally regulate many different targets to contribute to various biological characteristics of CSCs, such as proliferation, self-renewal, metastasis, and drug resistance. Therefore, E2Fs may be promising biomarkers and therapeutic targets associated with CSCs pathologies. Finally, exploring therapeutic strategies for E2Fs may result in disruption of CSCs, which may prevent tumor growth, metastasis, and drug resistance.

Breast cancer presents a variety of subtypes due to its cellular and molecular heterogeneity. The capacity of cancer cells to proliferate, invade, and metastasize depends not only on their intrinsic characters but also on their dynamic interaction with the host tumor microenvironment (TME), which includes immune cells. Meanwhile, the infiltration of immune cells in the TME severely affects the occurrence, development, treatment, and prognosis of breast cancer. Therefore, this review aims to explore the immune invasive tumor microenvironment in different intrinsic subtypes of breast cancer. Additionally, it highlights the mechanistic influence of the infiltrating immune cells on stage-wise dynamics of breast tumorigenesis. Moreover, the present review also attempts to discern the regulatory relationship between tumor infiltrating immune cells and immune microenvironment in different molecular subtypes of breast cancer, thus, spotlighting its clinical significance.

Lung cancer is the leading cause of cancer-related mortality worldwide due to its early asymptomatic and late metastasis. While cancer stem cells (CSCs) may play a vital role in oncogenesis and development of lung cancer, mechanisms underlying CSCs self‐renewal remain less clear. In the present study, we constructed a clinically relevant CSCs enrichment recognition model and evaluated the potential functions of phosphatidylinositol 3-kinase (PI3K)/AKT pathway (PI3K/AKT) and mitogen-activated protein kinases/extracellular signal-regulated kinase (MAPK/ERK) pathways in lung cancer via bioinformatic analysis, providing the basis for in depth mechanistic inquisition. Experimentally, we confirmed that PI3K/AKT pathway predominantly promotes proliferation through anti-apoptosis in lung adenocarcinoma cells, while MAPK/ERK pathway has an overwhelming superiority in regulating the proliferation in lung CSCs. Further, utilizing stemness score model, LLC-Symmetric Division (LLC-SD) cells and mouse orthotopic lung transplantation model, we elucidated an intricate cross-talk between the oncogenic pathway and the stem cell reprograming pathway that impact stem cell characteristics as well as cancer biology features of lung CSCs both in vitro and in vivo. In summary, our findings uncovered a new insight that PI3K/AKT and MAPK/ERK pathways as oncogenic signaling pathway and/or stem cell signaling pathway act distinctively and synergistically to regulate lung CSCs self-renewal.

The dichotomy of cancer-regulatory genes into “oncogenes (OCGs)” and “tumor-suppressor genes (TSGs)” has greatly helped us in learning molecular details of tumor biology. SPDEF, known as the prostate-derived ETS factor, is reported to play a pivotal role in normal cell development and survival, which has also been endowed with dual characteristics in cancers. Breast cancer (BC) is a highly heterogeneous disease which becomes the leading reason for cancer-related fatality among women worldwide. The involvement of SPDEF in many aspects of BC has been postulated, whereas the mechanism governing the regulation of the pro- and anti-oncogenic activities of SPDEF in BC state remains poorly defined. In this review, we summarized SPDEF as the double agent involving in expression profiles, the regulatory mechanism in BC progression, as well as the role in diagnosis, treatment and prognosis of BC. The understanding of SPDEF duality has contributed to gain insight into the tumor biology and also add a new dimension to the new therapy targets for BC.