Cancer Subtypes Research Articles

Expression and prognostic impact of hypoxia- and immune escape-related genes in triple-negative breast cancer: A comprehensive analysis.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer that lacks effective therapeutic options. Hypoxia and immune escape are critical factors that contribute to the progression of and resistance to therapy in patients with TNBC. Nevertheless, few studies have comprehensively analyzed hypoxia and immune escape in patients with TNBC. This study aimed to examine the expression of hypoxia- and immune escape-related genes in TNBC and their influence on prognosis. TNBC datasets were downloaded and processed from The Cancer Genome Atlas and Gene Expression Omnibus. Differential expression analysis identified 4949 differentially expressed genes, between TNBC and normal tissues. The intersection yielded 116 hypoxia- and immune escape-related differentially expressed genes (H&IERDEGs), including KIF4A, BIRC5, and BUB1. Enrichment analyses indicated that H&IERDEGs were significantly enriched in biological processes, including cell chemotaxis, leukocyte migration, and cytokine-cytokine receptor interaction. Subsequently, weighted gene co-expression network analysis identified 43 module genes that were found to define two TNBC subtypes. We constructed a prognostic risk model consisting of eight signature genes, which demonstrated a high predictive performance to predict the overall survival (OS) of patients with TNBC with an area under the curve (AUC) exceeding 0.9 at 1year survival. This indicates that the model effectively differentiates between outcomes, reflecting its robust performance. This study investigated the roles and potential mechanisms of hypoxia- and immune escape-related genes in TNBC and constructed a prognostic risk model with a high predictive performance. These findings offer novel molecular markers and potential therapeutic targets for TNBC.

Hypomethylating agents as emerging therapeutics for triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is recognized as the most aggressive subtype of breast cancer. Epigenetic silencing, such as DNA methylation mediated by DNA methyltransferases (DNMTs) plays key roles in TNBC tumorigenesis. Hypomethylating agents (HMAs) such as azacitidine, decitabine, and guadecitabine are key inhibitors of DNMTs, and accumulating evidence has shown their immunogenicity properties. In this review, the efficacy and anti-tumor immune responses triggered by HMAs in TNBC are presented and discussed. Essentially, overexpression of DNMTs is associated with poor prognosis and reduced TNBC survival rates, and these effects are negated by HMAs. In particular, HMAs could reverse epigenetic silencing of tumor suppressor genes and enhance immune recognition of TNBC cells. Clinical trials of HMAs in TNBCs are limited but early-stage trials indicate that HMAs are safe and tolerable. More clinical studies are required to establish the effectiveness of HMAs against the disease, as supported by preclinical data substantiating their effectiveness especially guadecitabine. Future research should focus on optimizing dosing and exploring combinations with immunotherapies to maximize the potential of HMAs in TNBC treatment.

TFAP2A Activates ADAM8 to Promote Lung Adenocarcinoma Angiogenesis Through the JAK/STAT Signaling Pathway.

As the most prevalent subtype of lung cancer, lung adenocarcinoma (LUAD) is closely associated with angiogenesis, which is fundamental to its progression. ADAM8 (A disintegrin and metalloproteinase 8) is an enzyme associated with tumor invasion, while its implications in LUAD angiogenesis are a field that awaits exploration. A thorough investigation into the impacts of ADAM8 on LUAD angiogenesis could contribute to the development of therapeutic drugs for LUAD. Bioinformatics delineated the expression profiles of TFAP2A and ADAM8 in LUAD tissues, focusing on ADAM8-enriched pathways. qRT-PCR confirmed their expression in LUAD cells. The CCK-8 assay was applied to gauge cell viability, and Western blot detected the presence of JAK2/STAT3 pathway proteins and VEGFR-2 and VEGF. Angiogenesis assays quantified the length of angiogenesis, and dual-luciferase and Chromatin immunoprecipitation assays verified the TFAP2A-ADAM8 binding. ADAM8 exhibited high expression in LUAD tissues and cells, with notable enrichment in the VEGF and JAK/STAT pathways. Cellular assays revealed that elevated ADAM8 expression enhanced cell viability, promoted the phosphorylation of JAK2 and STAT3, and boosted angiogenic capacity. The JAK inhibitor Peficitinib reversed the proangiogenic effects induced by ADAM8 overexpression. We also discovered overexpression of TFAP2A, an upstream transcription factor of ADAM8, in LUAD. Rescue experiments indicated that ADAM8 overexpression could counteract the inhibitory effects of TFAP2A knockdown on LUAD angiogenesis. This study reveals for the first time the critical role of ADAM8 in LUAD angiogenesis, demonstrating that TFAP2A promotes JAK/STAT pathway conduction by activating ADAM8. This finding not only provides a new perspective for understanding the pathogenesis of LUAD but also lays the foundation for the development of new therapies targeting ADAM8.

Machine Learning-based Lactate-Related Genes Signature Predicts Clinical Outcomes and Unveils Novel Therapeutic Targets in Esophageal Squamous Cell Carcinoma.

Esophageal squamous cell carcinoma (ESCC), a predominant subtype of esophageal cancer, typically presents with poor prognosis. Lactate is a crucial metabolite in cancer and significantly impacts tumor biology. Here, we aimed to construct a lactate-related prognostic signature (LPS) for predicting prognosis in ESCC and uncovering potential therapeutic targets. We designed a computational framework to identify lactate-related genes (LRGs) and applied machine-learning to generate an optimal LPS model from 103 combinations. The LPS was evaluated for its predictive accuracy regarding patient prognosis, chemotherapy, radiotherapy, and immunotherapy. Analysis also covered genomic and proteomic traits linked to LPS-defined subtypes. The LPS model demonstrated robust and reliable accuracy in predicting survival outcomes in patients with ESCC. Patients with low LPS scores exhibited a more favorable prognosis and an enhanced response to both chemotherapy and radiotherapy. Conversely, patients with high LPS scores exhibited increased sensitivity to BI-2536 and panobinostat. Furthermore, a low LPS score was associated with better prognosis in multiple immunotherapy datasets across cancer types. Genetic amplifications and deletions were detected more frequently in the high-LPS than in the low-LPS group; however, no significant correlation was observed with the tumor mutation burden. Knockdown of GATM, a key LRG, significantly inhibited cell viability, proliferative capacity, and migration and invasion abilities in ESCC cell lines. In conclusion, the LPS score can be used to predict the prognosis of patients with ESCC and facilitate a more precise approach for selecting patients likely to respond to treatment.

Metabolic Reprogramming and Adaption in Breast Cancer Progression and Metastasis.

Recent evidence has revealed that cancer is not solely driven by genetic abnormalities but also by significant metabolic dysregulation. Cancer cells exhibit altered metabolic demands and rewiring of cellular metabolism to sustain their malignant characteristics. Metabolic reprogramming has emerged as a hallmark of cancer, playing a complex role in breast cancer initiation, progression, and metastasis. The different molecular subtypes of breast cancer exhibit distinct metabolic genotypes and phenotypes, offering opportunities for subtype-specific therapeutic approaches. Cancer-associated metabolic phenotypes encompass dysregulated nutrient uptake, opportunistic nutrient acquisition strategies, altered utilization of glycolysis and TCA cycle intermediates, increased nitrogen demand, metabolite-driven gene regulation, and metabolic interactions with the microenvironment. The tumor microenvironment, consisting of stromal cells, immune cells, blood vessels, and extracellular matrix components, influences metabolic adaptations through modulating nutrient availability, oxygen levels, and signaling pathways. Metastasis, the process of cancer spread, involves intricate steps that present unique metabolic challenges at each stage. Successful metastasis requires cancer cells to navigate varying nutrient and oxygen availability, endure oxidative stress, and adapt their metabolic processes accordingly. The metabolic reprogramming observed in breast cancer is regulated by oncogenes, tumor suppressor genes, and signaling pathways that integrate cellular signaling with metabolic processes. Understanding the metabolic adaptations associated with metastasis holds promise for identifying therapeutic targets to disrupt the metastatic process and improve patient outcomes. This chapter explores the metabolic alterations linked to breast cancer metastasis and highlights the potential for targeted interventions in this context.

Cells-of-Origin of Breast Cancer and Intertumoral Heterogeneity.

Both intrinsic and extrinsic mechanisms underpin the profound intertumoral heterogeneity in breast cancer. Increasing evidence suggests that the intrinsic characteristics of breast epithelial precursor cells may influence tumour phenotype. These "cells-of-origin" of cancer preside in normal breast tissue and are uniquely susceptible to mutagenesis upon exposure to distinct oncogenic stimuli. Notably, molecular profiling studies have revealed strong concordance between the gene expression profiles of breast cancer subtypes and discrete cell types within the normal breast epithelium. Further characterisation of cells-of-origin of breast cancer requires comprehensive delineation of the normal mammary stem cell hierarchy. To this end, mouse models have provided valuable tools for exploring stem and progenitor cell function and identifying potential targets of neoplastic transformation via in vivo lineage-tracing studies. Nonetheless, the murine mammary differentiation hierarchy does not fully recapitulate human biology, and complementary studies using patient-direct breast tissue are critical. There is also accumulating evidence that extrinsic factors such as the microenvironment of premalignant cells can influence tumour initiation, highlighting opportunities for targeting cancer cells-of-origin via deconvolution of the premalignant epithelial niche. Pertinently, the identification of premalignant clones and targetable molecular perturbations responsible for driving their oncogenic transformation has critical implications for disease management and prevention.

LASSO-mCGA: Machine Learning and Modified Compact Genetic Algorithm-Based Biomarker Selection for Breast Cancer Subtype Classification

LASSO-mCGA: Machine Learning and Modified Compact Genetic Algorithm-Based Biomarker Selection for Breast Cancer Subtype Classification

CDKN3 as a key regulator of G2M phase in triple-negative breast cancer: Insights from multi-transcriptomic analysis.

Triple-negative breast cancer (TNBC) remains a significant global health challenge, emphasizing the need for precise identification of patients with specific therapeutic targets and those at high risk of metastasis. This study aimed to identify novel therapeutic targets for personalized treatment of TNBC patients by elucidating their roles in cell cycle regulation. Using weighted gene co-expression network analysis (WGCNA), we identified 83 hub genes by integrating gene expression profiles with clinical pathological grades. A machine learning-based integrative approach further pinpointed 12 prognostic genes, among which CDKN3 exhibited the highest hazard ratio and the most adverse impact on overall survival (OS) in BC patients. Additionally, CDKN3 was identified as an independent prognostic factor for OS prediction. CDKN3 overexpression was confirmed in BC patients and validated at both mRNA and protein levels in BC cells. Knockdown of CDKN3 significantly inhibited the migration and proliferation of BC cells. Cell cycle pathway analysis revealed significant enrichment in G2M-associated pathways in BC patients, with multi-transcriptomic data indicating a close association between enhanced G2M cell cycle activity and CDKN3 upregulation in basal cancer subtypes. Pseudotime analysis further suggested CDKN3 upregulation during the G2M phase at the terminal trajectory of basal cancer subtypes, implying that CDKN3 may drive BC cell progression by promoting G2M cell cycle activity. Mechanistically, CDKN3 knockdown induced G2M cell cycle arrest in TNBC cells by downregulating CCNB2. In conclusion, CDKN3 knockdown effectively inhibits TNBC by arresting the G2M cell cycle, underscoring CDKN3 as a promising therapeutic target in TNBC treatment.

Integrated bioinformatic approach of Balur therapy for breast cancer subtypes

Integrated bioinformatic approach of Balur therapy for breast cancer subtypes

CSSEC: An adaptive approach integrating consensus and specific self-expressive coefficients for multi-omics cancer subtyping

CSSEC: An adaptive approach integrating consensus and specific self-expressive coefficients for multi-omics cancer subtyping

S6K1 is a Targetable Vulnerability in Tumors Exhibiting Plasticity and Therapy Resistance.

Background: Most tumors initially respond to treatment, yet refractory clones subsequently develop owing to resistance mechanisms associated with cancer cell plasticity and heterogeneity. Methods: We used a chemical biology approach to identify protein targets in cancer cells exhibiting diverse driver mutations and representing models of tumor lineage plasticity and therapy resistance. An unbiased screen of a drug library was performed against cancer cells followed by synthesis of chemical analogs of the most effective drug. The cancer subtype target range of the leading drug was determined by PRISM analysis of over 900 cancer cell lines at the Broad Institute, MA. RNA-sequencing and enrichment analysis of differentially expressed genes, as well as computational molecular modeling and pull-down with biotinylated small molecules were used to identify and validate RPS6KB1 (p70S6K or S6K1) as an essential target. Genetic restoration was used to test the functional role of S6K1 in cell culture and xenograft models. Results: We identified a novel derivative of the antihistamine drug ebastine, designated Super-ebastine (Super-EBS), that inhibited the viability of cancer cells representing diverse KRAS and EGFR driver mutations and models of plasticity and treatment resistance. Interestingly, PRISM analysis indicated that over 95% of the diverse cancer cell lines tested were sensitive to Super-EBS and the predicted target was the serine/threonine kinase S6K1. S6K1 is upregulated in various cancers relative to counterpart normal/benign tissues and phosphorylated-S6K1 predicts poor prognosis for cancer patients. We noted that inhibition of S6K1 phosphorylation was necessary for tumor cell growth inhibition, and restoration of phospho-S6K1 rendered tumor cells resistant to Super-EBS. Inhibition of S6K1 phosphorylation by Super-EBS induced caspase-2 dependent apoptosis via inhibition of the Cdc42/Rac-1/p-PAK1 pathway that led to actin depolymerization and caspase-2 activation. The essential role of S6K1 in the action of Super-EBS was recapitulated in xenografts, and knockout of S6K1 abrogated tumor growth in mice. Conclusion: S6K1 is a therapeutic vulnerability in tumors exhibiting intrinsic and/or acquired resistance to treatment.

Advances in Therapy for Urothelial and Non-Urothelial Subtype Histologies of Advanced Bladder Cancer: From Etiology to Current Development.

Urothelial carcinoma (UC) is the most common histological subtype of bladder tumors; however, bladder cancer represents a heterogeneous group of diseases with at least 40 distinct histological subtypes. Among these, the 2022 World Health Organization classification of urinary tract tumors identifies a range of less common subtypes of invasive UC, formerly known as variants, which are considered high-grade tumors, including squamous cell, small-cell, sarcomatoid urothelial, micropapillary, plasmacytoid, and urachal carcinomas, and adenocarcinoma. Their accurate histological diagnosis is critical for risk stratification and therapeutic decision-making, as most subtype histologies are associated with poorer outcomes than conventional UC. Despite the importance of a precise diagnosis, high-quality evidence on optimal treatments for subtype histologies remains limited owing to their rarity. In particular, neoadjuvant and adjuvant chemotherapy have not been well characterized, and prospective data are scarce. For advanced-stage diseases, clinical trial participation is strongly recommended to address the lack of robust evidence. Advances in molecular pathology and the development of targeted therapies and immunotherapies have reshaped our understanding and classification of bladder cancer subtypes, spurring efforts to identify predictive biomarkers to guide personalized treatment strategies. Nevertheless, the management of rare bladder cancer subgroups remains challenging because they are frequently excluded from clinical trials. For localized disease, curative options such as surgical resection or radiotherapy are available; however, treatment options become more limited in recurrence or metastasis, where systemic therapy is primarily used to control disease progression and palliate symptoms. Herein, we present recent advances in the management of urothelial and non-urothelial bladder cancer subtypes and also explore the current evidence guiding their treatment and emphasize the challenges and perspectives of future therapeutic strategies.

Creating a Fluorescent “AND” Logic Gate Aptamer Platform for Identifying Exosomes Derived from Breast Cancer Subtypes

Creating a Fluorescent “AND” Logic Gate Aptamer Platform for Identifying Exosomes Derived from Breast Cancer Subtypes

Long-term outcome for neoadjuvant versus adjuvant chemotherapy in early breast cancer and the prognostic impact of nodal therapy response: A population-based study.

Although neoadjuvant systemic treatment for non-metastatic breast cancer has gained ground during the past decade, there is no compelling evidence that it improves overall survival compared to primary tumor resection and adjuvant treatment. At the same time, the approach to responders to neoadjuvant treatment in the axilla is evolving. This is a retrospective analysis of a prospectively collected population-based registry. Patients that received neoadjuvant (n=2126) or adjuvant chemotherapy (n=4754) for non-metastatic breast cancer during 2007-2020 in the Stockholm-Gotland region, which comprises 25% of the entire Swedish population, were included. Overall survival of patients treated preoperatively and postoperatively was compared using inverse probability treatment weighting and landmark analysis. The prognostic impact of change between prechemotherapy clinical to postchemotherapy pathologic nodal stage (cN/pN) in women receiving neoadjuvant treatment was investigated. Median follow-up was 4.93 years. There was no difference in adjusted overall survival between adjuvant (reference) and neoadjuvant treatment in the entire population (HR=1.38, 95% CI 0.98-1.93, p=0.062) or in breast cancer subtypes. Patients converting from positive clinical to negative pathologic nodal stage (cN+/pN0) had improved outcomes compared to cN0/pN0 or patients with pN0 following primary surgery. These patients had a particular disease trajectory, with early peak in risk of death followed by quick and sustained decrease. There was no difference in survival of patients treated with neoadjuvant versus adjuvant systemic therapy for non-metastatic breast cancer. Patients with cN+/pN0 have excellent prognosis and represent potential candidates for de-escalation of local and systemic treatment.

Preliminary characterisation of the spatial immune and vascular environment in triple negative basal breast carcinomas using multiplex fluorescent immunohistochemistry.

Triple negative breast cancers often contain higher numbers of tumour-infiltrating lymphocytes compared with other breast cancer subtypes, with their number correlating with prolonged survival. Since little is known about tumour-infiltrating lymphocyte trafficking in triple negative breast cancers, we investigated the relationship between tumour-infiltrating lymphocytes and the vascular compartment to better understand the immune tumour microenvironment in this aggressive cancer type. We aimed to identify mechanisms and signaling pathways responsible for immune cell trafficking in triple negative breast cancers, specifically of basal type, that could potentially be manipulated to change such tumours from immune "cold" to "hot" thereby increasing the likelihood of successful immunotherapy in this challenging patient population. We characterised the spatial immune environment in 10 basal breast cancers showing a range of tumour-infiltrating lymphocytes using multiplex fluorescent immunohistochemistry and quantitative digital analysis of CD3+ T cells. We examined their relationship to blood vessels and their activation status as defined by VCAM-1, ICAM-1 and PD-L1. Confirmation of the relationship between tumour-infiltrating lymphocytes and endothelial activation was performed through in silico analysis on TCGA BRCA RNA-seq data (N = 808). Significantly higher CD3+ T cell densities were observed in the stromal compartment compared with the neoplastic cell compartment (P = 0.003). ICAM-1 activated blood vessels were spatially associated with higher CD3+ T cell densities only within 30 microns of blood vessels compared with more distal activated and non-activated blood vessels (P = 0.041). In silico analysis confirmed higher numbers of tumour-infiltrating lymphocytes in basal breast cancers and that higher numbers were significantly associated with endothelial cell activation molecules, co-clustering with upregulated ICAM-1 and VCAM-1 amongst others. PD-L1 was also identified in a subset of blood vessels, suggesting an additional immune regulatory mechanism in endothelial cells. Regulating the activation status of tumour-associated vascular endothelial cells may improve T cell trafficking into basal breast tumours and enhance immunotherapeutic response.

Recent advances of antibody-drug conjugates in treating breast cancer with different HER2 status.

Despite the availability of multiple treatment options for breast cancer, challenges such as adverse events, drug resistance, and disease progression persist for patients. The identification of human epidermal growth factor receptor 2 (HER2) as an oncogenic driver in a subset of breast cancers, alongside the development of HER2-targeted therapies, has significantly improved the prognosis of HER2-amplified breast cancers. However, therapeutic options remain limited for HER2-overexpressing or HER2-negative breast cancers. In response to this gap, antibody-drug conjugates (ADCs) have emerged as a promising approach. ADCs combine the specificity of monoclonal antibodies with the cytotoxic effects of chemotherapy, which allows for the targeted delivery of a cytotoxic payload to cancer cells. ADCs have been used as adjuvant chemotherapeutic treatments and salvage therapies across various breast cancer subtypes, which have greatly improved the prognosis of breast cancer patients. Numerous ongoing clinical trials seek to optimize dosing strategies and identify patient populations that would benefit most from ADCs. This review presents an updated and comprehensive overview of emerging investigational ADCs for treating breast cancer patients with various HER2 subtypes. These ADCs are spearheading a new era in targeted cancer therapy, promising to innovate treatment paradigms for both HER2-positive and HER2-low breast cancers.

Insights into the Emerging Therapeutic Targets of Triple-negative Breast Cancer.

Triple-negative Breast Cancer (TNBC), the most aggressive breast cancer subtype, is characterized by the non-appearance of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Clinically, TNBC is marked by its low survival rate, poor therapeutic outcomes, high aggressiveness, and lack of targeted therapies. Over the past few decades, many clinical trials have been ongoing for targeted therapies in TNBC. Although some classes, such as Poly (ADP Ribose) Polymerase (PARP) inhibitors and immunotherapies, have shown positive therapeutic outcomes, however, clinical effects are not much satisfiable. Moreover, the development of drug resistance is the major pattern observed in many targeted monotherapies. The heterogeneity of TNBC might be the cause for limited clinical benefits. Hence,, there is a need for the potential identification of new therapeutic targets to address the above limitations. In this context, some novel targets that can address the above-mentioned concerns are emerging in the era of TNBC therapy, which include Hypoxia Inducible Factor (HIF-1α), Matrix Metalloproteinase 9 (MMP-9), Tumour Necrosis Factor-α (TNF-α), β-Adrenergic Receptor (β-AR), Voltage Gated Sodium Channels (VGSCs), and Cell Cycle Regulators. Currently, we summarize the ongoing clinical trials and discuss the novel therapeutic targets in the management of TNBC.

Deep Learning and Radiomics in Triple-Negative Breast Cancer: Predicting Long-Term Prognosis and Clinical Outcomes.

Triple-negative breast cancer (TNBC) is a unique breast cancer subtype characterized by the lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression in tumor cells. TNBC represents about 15% to 20% of all breast cancers and is aggressive and highly malignant. Currently, TNBC diagnosis primarily depends on pathological examination, while treatment efficacy is assessed through imaging, biomarker detection, pathological evaluation, and clinical symptom improvement. Among these, biomarker detection and pathological assessments are invasive, time-intensive procedures that may be difficult for patients with severe comorbidities and high complication risks. Thus, there is an urgent need for new, supportive tools in TNBC diagnosis and treatment. Deep learning and radiomics techniques represent advanced machine learning methodologies and are also emerging outcomes in the medical-engineering field in recent years. They are extensions of conventional imaging diagnostic methods and have demonstrated tremendous potential in image segmentation, reconstruction, recognition, and classification. These techniques hold certain application prospects for the diagnosis of TNBC, assessment of treatment response, and long-term prognosis prediction. This article reviews recent progress in the application of deep learning, ultrasound, MRI, and radiomics for TNBC diagnosis and treatment, based on research from both domestic and international scholars.

Treatment Approach for Rare Histologic Subtypes of Breast Cancer: A Review

Rare histological subtypes of breast cancer introduce unique challenges to treatment and require a more personalized approach. Subtypes with favorable prognoses, such as mucinous, tubular, and cribriform carcinomas, generally respond well to less aggressive treatments such as endocrine therapy. However, certain triple-negative breast cancer subtypes that are typically considered aggressive also demonstrate unexpectedly better outcomes in specific cases. Conversely, more aggressive subtypes, including invasive micropapillary carcinoma and high-grade metaplastic breast cancer, often present greater treatment challenges due to their resistance to conventional therapies. Recent advancements in targeted treatments, such as immune checkpoint inhibitors, have shown promise in improving outcomes in some of these difficult cases. This review emphasizes the need for ongoing research and a tailored approach that considers both molecular and histological characteristics to improve the management and survival outcomes of patients with these rare and complex breast cancer subtypes.

The anticancer mechanisms of Toxoplasma gondii rhoptry protein 16 on lung adenocarcinoma cells

ABSTRACT Lung adenocarcinoma is the most prevalent subtype of lung cancer, which is the leading cause of cancer-related mortality worldwide. Toxoplasma gondii (T.gondii) Rhoptry protein 16 (ROP16) has been shown to quickly enter the nucleus, and through activate host cell signaling pathways by phosphorylation STAT3 and may affect the survival of tumor cells. This study constructed recombinant lentiviral expression vector of T. gondii ROP16 I/II/III and stably transfected them into A549 cells, and the effects of ROP16 on cell proliferation, cell cycle, apoptosis, invasion, and migration of A549 cells were explored by utilizing CCK-8, flow cytometry, qPCR, Western blotting, TUNEL, Transwell assay, and cell scratch assay, and these effects were confirmed in the primary human lung adenocarcinoma cells from postoperative cancer tissues of patients. The type I and III ROP16 activate STAT3 and inhibited A549 cell proliferation, regulated the expression of p21, CDK6, CyclinD1, and induced cell cycle arrest at the G1 phase. ROP16 also regulated the Bax, Bcl-2, p53, cleaved-Caspase3, and Caspase9, inducing cell apoptosis, and reduced the invasion and migration of A549 cells, while type II ROP16 protein had no such effect. Furthermore, in the regulation of ROP16 on primary lung adenocarcinoma cells, type I and III ROP16 showed the same anticancer potential. These findings confirmed the anti-lung adenocarcinoma effect of type I and III ROP16, offering fresh perspectives on the possible application of ROP16 as a target with adjuvant therapy for lung adenocarcinoma and propelling the field of precision therapy research toward parasite treatment of tumors.