Lung adenocarcinoma (LUAD) is the most prevalent form of lung cancer worldwide. Due to the lack of clinically useful molecular biomarkers, the diagnosis and prognosis of patients with LUAD remain poor. Patients with LUAD often exhibit abnormalities in the levels of coagulation factors. Therefore, the objective of the present study was to develop a model based on coagulation-related factors in LUAD. Gene expression data and clinical information from 582 patients with LUAD were obtained from The Cancer Genome Atlas (TCGA). A set of 138 coagulation-related genes (CRGs) was retrieved from The Molecular Signatures Database, and their expression levels were examined in TCGA dataset to identify differentially expressed CRGs. Predictive models were constructed using least absolute shrinkage and selection operator-Cox regression. The risk score from the model was used to establish high- and low-risk patient groups. Additionally, Kaplan-Meier analyses were performed to evaluate the differences in overall survival (OS) and progression-free survival between the two groups. The accuracy of the model was verified through receiver operating characteristic and principal component analysis. In addition, the tumor immune dysfunction and exclusion algorithm was used to assess immune escape and immunotherapy responses in relation to the CRGs. A predictive model comprising four genes, namely matrix metalloproteinase (MMP) 1, MMP10, cathepsin V and thrombin, was established to estimate the survival rate of patients with LUAD. The OS rates of patients in the high-risk group were lower compared with those in the low-risk group. Furthermore, a combination of high-risk score and low tumor mutation burden was associated with the poorest survival in patients with LUAD. Patients in different risk groups exhibited different drug sensitivities based on their risk scores. In conclusion, the four-gene based prognostic model served as an independent predictor of survival rates in patients with LUAD and may offer a novel approach for prognosis and treatment.

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer mortality. Despite advancements in gene targeted therapies and immunotherapies, high heterogeneity contributes to limited efficacy and therapeutic resistance. Ubiquitination, a crucial post-translational modification that regulates protein stability and degradation, plays a significant role in cancer pathogenesis by influencing key oncogenic pathways and tumour progression. This review systematically explores the ubiquitin-proteasome system (UPS) and its potential as a therapeutic target for NSCLC. We highlight recent preclinical and clinical studies focusing on ubiquitination-related biomarkers, drug targets and emerging therapies like proteasome inhibitors and Proteolysis-targeting chimeras (PROTACs). By exploring the impact of the UPS on tumour biology, the progression of NSCLC and its response to therapy, we aim to underscore the potential of targeting the ubiquitination-deubiquitination system as a complementary or synergistic approach to existing therapeutic strategies in NSCLC, thereby enhancing patient outcomes and overcoming treatment resistance.

Ribonucleic acid (RNA)-based therapies represent a promising class of drugs for the treatment of non-small cell lung cancer (NSCLC) due to their ability to modulate gene expression. Therapies leveraging small interfering RNA (siRNA), messenger RNA (mRNA), microRNA (miRNA), and antisense oligonucleotides (ASOs) offer various advantages over conventional treatments, including the ability to target specific genetic mutations and the potential for personalized medicine approaches. However, the clinical translation of these therapeutics for the treatment of NSCLC faces challenges in delivery due to their immunogenicity, negative charge, and large size, which can be mitigated with delivery platforms. In this review, we provide a description of the pathophysiology of NSCLC and an overview of RNA-based therapeutics, specifically highlighting their potential application in the treatment of NSCLC. We discuss relevant classes of RNA and their therapeutic potential for NSCLC. We then discuss challenges in delivery and non-viral delivery strategies such as lipid- and polymer-based nanoparticles that have been developed to address these issues in preclinical models. Furthermore, we provide a summary table of clinical trials that leverage RNA therapies for NSCLC [which includes their National Clinical Trial (NCT) numbers] to highlight the current progress in NSCLC. We also discuss how these NSCLC therapies can be integrated with existing treatment modalities to enhance their efficacy and improve patient outcomes. Overall, we aim to highlight non-viral strategies that tackle RNA delivery challenges while showcasing RNA's potential as a next-generation therapy for NSCLC treatment.

This retrospective study was undertaken to assess the predictive efficacy of 18F-FDG PET/CT -derived radiomic features concerning the co-mutation status of epidermal growth factor receptor (EGFR) and TP53 in LUAD.

A cohort of 150 LUAD patients underwent pretreatment 18F-FDG PET/CT scans with known mutation status of EGFR and TP53 were collected. The feature extraction based on their PET/CT images utilized the Pyradiomics package based on the 3D Slicer. The optimal radiomic features were selected through correlation analysis and the Gradient Boosting Decision Tree (GBDT) algorithm, followed by the construction of the radiomic model. The clinical model incorporated meaningful clinical variables, whereas the complex model integrated both the radiomic and clinical models. The area under the receiver operating characteristic curve (AUC) facilitated the comparison of prediction performance across the three models. The DCA gauged the clinical utility of these models.

The patient cohort was randomly allocated into a training set (n = 105) and a validation set (n = 45) in a 7:3 ratio. Eleven PET and eleven CT optimal radiomic features were selected to construct the radiomic model. The model showed a good ability to discriminate the co-occurrence of EGFR and TP53, with AUC equal to 0.850 in the training set, and 0.748 in the validation set, compared with 0.750 and 0.626 for the clinical model. The complex model exhibited the highest AUC values, with 0.880 and 0.794 in both sets, but there were no significant differences compared to the radiomic model. The DCA revealed favorable clinical value.

Cancer 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.

LUAD 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.

40 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.

This 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.

Hepatocellular carcinoma (HCC) is a malignant disease with high incidence and mortality worldwide. This study focuses on the TP53 target protein to investigate the potential therapeutic effect of tetrahydrocurcumin (THC) on HCC and its mechanism of action. The research hypothesis is that THC can inhibit the proliferation, migration, and invasion of HCC cells, and promote their apoptosis by regulating the TP53 target protein.

To explore the mechanism by which THC inhibits HCC cell proliferation via the TP53 signaling pathway.

Potential targets of THC and HCC were identified from multiple databases. The core targets were subjected to analyses using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, and visualization processing, using the online platform Metascape to identify the key molecules and signaling pathways involved in the action of THC against HCC. The molecular mechanisms of action of THC against TP53 in the inhibition of HCC cells were verified using cell counting kit-8, Transwell, apoptosis, and western blotting assays.

Molecular docking results showed that THC had a high score for the TP53 target protein. In vitro experiments indicated that THC effectively inhibited the proliferation and migration of HCC cells, and affected the expression levels of TP53, MDM2, cyclin B, Bax, Bcl-2, caspase-9, and caspase-3.

THC induces the apoptosis of HCC cells through the TP53 signaling pathway, thereby inhibiting their proliferation and migration.

Therapeutic challenges persist in the management of non-small cell lung cancer (NSCLC) in oncology. Camptothecins have demonstrated as crucial agents in tumor therapy; however, their efficacy is significantly hindered by adverse effects and drug resistance. Herein, we present a novel camptothecin derivative named 9c, which exhibits impressive anti-NSCLC potency surpassing the widely recognized camptothecin analog FL118 through a novel mechanism. Our findings demonstrated that 9c effectively inhibited tumor malignancy through cell cycle arrest and apoptosis induction with the transcriptional downregulation of anti-apoptotic genes including survivin, Mcl-1, Bcl-2, and XIAP. Mechanistically, 9c induced a wild-type p53 expression by destabilizing the NSA2-EGFR axis, thus delaying the cell cycle progression and ultimately triggering apoptosis. 9c significantly inhibited the growth of the NSCLC xenograft in vivo without observed side toxicity. Importantly, it complemented the therapeutic advantages of the novel drug AMG510 for addressing KRAS-mutant NSCLC. Collectively, these findings position 9c as a promising candidate with innovative approaches to combat NSCLC.

HER2 mutations are critical drivers of non-small cell lung cancer (NSCLC), affecting 2 %-3 % of patients and often leads to poor prognosis and limited response to conventional therapies. This study investigates the genomic characteristics and prognostic relevance of dynamic circulating tumor DNA (ctDNA) monitoring in advanced NSCLC patients with HER2 mutations treated with pyrotinib and apatinib.

The PATHER2 study included 33 advanced NSCLC patients harboring HER2 mutations or amplification, who received combination therapy of pyrotinib and apatinib. Among them, 27 patients had baseline blood samples available for analysis. Baseline blood samples (n = 27), follow-up samples after one treatment cycle (n = 13), and samples upon disease progression (n = 18) were collected. ctDNA was extracted and sequenced using a 556-gene panel.

At baseline, HER2 mutations were detected in 21 of 27 patients through ctDNA, and 19 showed consistent results between tissue and blood sample testing. Patients with TP53 and DNMT3A alterations at baseline had significantly shorter progression-free survival (PFS). Dynamic ctDNA monitoring revealed that patients without detectable HER2 mutations after one treatment cycle had longer PFS and a trend toward longer overall survival (OS) compared to those with persistent HER2 mutations. The newly emerged mutations after resistance were infrequently found in HER2, instead primarily enriched in the chromatin remodeling pathway.

ctDNA holds significant value in guiding the treatment of patients with HER2 mutations. Baseline TP53 and DNMT3A alterations, along with persistent HER2 mutations after initial treatment, are associated with poorer prognosis. The primary mechanism of resistance to pyrotinib and apatinib in these patients may be attributed to chromatin remodeling rather than on-target alterations.

Lung cancer remains a leading cause of global cancer-related mortality, and the exploration of innovative therapeutic approaches, such as PD1/PDL1 immunotherapy, is critical. This study leverages comprehensive data from the Cancer Genome Atlas (TCGA) to investigate the differential expression of PD1/PDL1 in lung cancer patients and explores its implications. Clinical data, RNA expression, somatic mutations, and copy number variations of 1017 lung cancer patients were obtained from TCGA. Patients were categorized into high (HE) and low (LE) PD1/PDL1 expression groups based on mRNA levels. Analyses included differential gene expression, functional enrichment, protein-protein interaction networks, and mutational landscape exploration. The study identified 391 differentially expressed genes, with CD4 and PTPRC among the upregulated genes in the HE group. Although overall survival did not significantly differ between HE and LE groups, enrichment analysis revealed a strong association with immunoregulatory signaling pathways, emphasizing the relevance of PD1/PDL1 in immune response modulation. Notably, TP53 mutations were significantly correlated with high PD1/PDL1 expression. This study provides a comprehensive analysis of PD1/PDL1 expression in lung cancer, uncovering potential biomarkers and highlighting the intricate interplay between PD1/PDL1 and the immune response. The identified upregulated genes, including CD4 and PTPRC, warrant further investigation for their roles in the context of lung cancer and immunotherapy. The study underscores the importance of considering molecular heterogeneity in shaping personalized treatment strategies for lung cancer patients. Limitations, such as the retrospective nature of TCGA data, should be acknowledged.

Lung cancer is the most common malignant tumor in China. In 2016, more than 800,000 new cases of lung cancer were diagnosed in China. Squamous cell carcinoma of the lung, a type of non-small cell lung cancer (NSCLC), accounts for 25-30% of all lung cancer cases, and has an overall 5-year survival rate of about 32.53%, lower than adenocarcinoma for which there have been far more therapeutic advances in the last few decades. The purpose of this study was to explore the mechanisms of the disease and to identify potential prognostic biomarkers.

This study analyzed lung squamous cell carcinoma of the lung tissues and paraneoplastic tissues to identify differentially expressed genes (DEGs). We conducted a Gene Set Enrichment Analysis and prognostic analysis by constructing competing endogenous RNA (ceRNA) networks; we performed a correlation analysis of the target genes and verified the targeting relationship of the ceRNA by cellular assays. We assessed the effects of the target genes on tumor cell proliferation, invasion and apoptosis by Cell Counting Kit-8 (CCK-8) assays, invasion assays, and caspase 3/7 assays, respectively.

We identified 4,039 downregulated genes and 1,924 upregulated genes. The p53 pathway, cell-cycle pathway and mismatch-repair (MMR) pathway were activated, while the mitogen-activated protein kinase pathway was inhibited. Two ceRNA networks centered on the long non-coding RNAs (lncRNAs) MAGI2-AS3 and LINC01089 were constructed. MAGI2-AS3 was found to regulate five messenger RNAs (mRNAs) (i.e., MBNL2, ATP5L, FAM103A1, MDH1, and STXBP1) through three microRNAs (miRNAs), whereas LINC01089 was found to regulate six mRNAs (i.e., ZFP36L2, APBB2, PDLIM3, MYADM, PHF5A, and SLC26A9) through two miRNAs. The expression of these lncRNAs and mRNAs was significantly associated with prognosis (P<0.05). A significant correlation was also found between the expression of MAGI2-AS3 and MBNL2 (R=0.51), and both signatures were also significantly associated with prognosis. We also found that MAGI2-AS3 and MBNL2 had a regulatory relationship at the cellular level, for example, high expression of MBNL2 was noted to inhibit cancer cell proliferation and migration yet promote apoptosis.

MAGI-AS3 and MBNL2 are both differentially expressed in squamous cell carcinoma of the lung and are potential prognostic markers. A significant association was also found between MAGI2-AS3 and the expression of MBNL2 (R=0.51). High expression of MBNL2 inhibits cancer cell proliferation and migration, yet promotes cancer cell apoptosis.

Alterations in the methylation of genetic material can influence carcinogenesis by the downregulation or overexpression of ADAMTS (a disintegrin-like and metalloprotease with thrombospondin motifs) protease genes. Through their proteolytic activity, these enzymes are also capable of promoting angiogenesis. Consequently, ADAMTS proteases can either facilitate or inhibit cancer progression. This study aimed to evaluate the methylation levels of the ADAMTS6, ADAMTS9, and ADAMTS12 genes in non-small-cell lung cancer (NSCLC) using data from bioinformatics databases. The focus was on differences between lung adenocarcinoma (LUAD) and lung squamous-cell carcinoma (LUSC) subtypes and their impact on patient overall survival (OS). ADAMTS6 gene expression is significantly reduced in LUSC, and analysis of ADAMTS9 gene expression showed a significantly reduced gene transcript level in LUAD and LUSC, while both NSCLC subtypes demonstrated ADAMTS12 upregulation. In LUSC, significantly elevated promoter methylation was found in all of the aforementioned genes, while in LUAD, higher promoter methylation was observed only for ADAMTS9 and ADAMTS12. The differential methylation region (DMR) pattern demonstrated by ADAMTS6, ADAMTS9, and ADAMTS12 is a useful tool for distinguishing normal from cancer cells. The areas under the curve (AUCs) ranged from 0.86 to 0.99 for both LUAD and LUSC subtypes. The methylation level of different CpG sites among selected ADAMTS members is related to patient survival, suggesting it may have value as a prognostic marker. The methylation degree of promoter regions in genes encoding ADAMTS family proteins could significantly influence LUSC and LUAD. Increased promoter methylation could also reduce certain gene expression, contributing to cancer progression. The expression levels and specific DMRs of ADAMTS genes may serve as prognostic markers correlating with patient OS. Assessing ADAMTS gene methylation could become a diagnostic tool for differentiating NSCLC subtypes and potentially guide therapeutic strategies. Further research is needed to fully understand the activity and mechanisms of ADAMTS family proteins.

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths worldwide. Mutations within the TP53 gene represent critical molecular events in NSCLC, contributing to the tumorigenesis in the pulmonary epithelial tissues. TP53 is a widely researched prognostic indicator in NSCLC, and pathological investigations have revealed a weak to mild negative predictive effect for TP53. Mutated p53 protein may have some pro-oncogenic impact, and the variations may change tumor inhibitors into oncogenes. The diverse mutational spectrum of TP53 in NSCLC with different mutations is linked to varied treatment responses. In contrast, first-line chemotherapeutics to this progress are limited, however, randomized trials with new chemotherapeutics have shown significant survival benefits. This review highlighted the critical influence of TP53 gene mutations on pathological-sensitivity and overall survival outcomes in NSCLC. Further research is needed to explore TP53 mutation-specific pathways and their effects on NSCLC progression and treatment effectiveness.

Globally, breast and ovarian cancers are major health concerns in women and account for significantly high cancer-related mortality rates. Dysregulations and mutations in genes like TP53, BRCA1/2, KRAS and PTEN increase susceptibility towards cancer. Here, we discuss the impact of mutations in the key regulatory gene, TP53 and polymorphisms in its negative regulator MDM2 which are reported to accelerate cancer progression. Missense mutations, null mutations, transversions, transitions, and point mutations occurring in the TP53 gene can cause an increase in metastatic activity. This review discusses mutations occurring in exon regions of TP53, polymorphisms in MDM2 and their interaction with large ribosomal subunit protein (RPL) leading to cancer development. We also highlight the potential of small molecules e.g. p53 activators like XI-011, Tenovin-1, and Nutlin-3a for the treatment of breast and ovarian cancers. The therapeutic efficacy of natural compounds in amelioration of these two types of cancers is also discussed.

Brain metastases (BMs) are the most common intracranial tumors in adults and occur 3-10 times more frequently than primary brain tumors. Despite intensive multimodal therapies, including resection, radiotherapy, and chemotherapy, BMs are associated with poor prognosis and remain challenging to treat. BMs predominantly originate from primary lung (20-56%), breast (5-20%), and melanoma (7-16%) tumors, although they can arise from other cancer types less frequently. The metastatic cascade is a multistep process involving local invasion, intravasation into the bloodstream or lymphatic system, extravasation into normal tissue, and colonization of the distal site. After reaching the brain, circulating tumor cells (CTCs) breach the blood-brain barrier (BBB).The selective permeability of the BBB poses a significant challenge for therapeutic compounds, limiting the treatment efficacy of BMs. Understanding the mechanisms of tumor cell interactions with the BBB is crucial for the development of effective treatments. This review provides an in-depth analysis of the brain barriers, including the BBB, blood-spinal cord barrier, blood-meningeal barrier, blood-arachnoid barrier, and blood-cerebrospinal fluid barrier. It explores the molecular and cellular components of these barriers and their roles in brain metastasis, highlighting the importance of this knowledge for identifying druggable targets to prevent or limit BM formation.

Human Lung Carcinoma (LC) is among the most diagnosed cancers across the world among those non-small cell lung cancer (NSCLC) comprises about 85%. Next Generation Sequencing based detection of mutations are now well established in molecular oncology. With the advent of modern diagnostic methods, it is now well known that there are several mutations and gene rearrangements which are associated with the development of LC. Among those mutations, TP53 is the most prevalent with the concomitant EGFR mutation.

In this retrospective study, a total number of 414 patients have been incorporated who have attended RGCIRC in the period between November 2015 to March 2024. Clinical stage has been determined as per NCCN Guideline version 2.2024. Nucleic Acid (DNA and RNA) from FFPE samples were extracted and detection of mutation was performed by Next generation sequencing (NGS) method.

All 414 patients opted for the customised NGS panel for lung cancer among those 203 patients were TP53 mutation and 87 patients were EGFR mutation positive. 62 patients were TP53-EGFR double mutation positive. The results of this study have shown that TP53 mutated patients show poor prognosis with conventional therapy. However, TP53-EGFR co-mutated patient's recovery rates are comparatively promising due to the availability of the targeted therapy of EGFR.

Studies have shown that TP53 mutation is unlikely to derive clinical benefit in LC patients and shows poorer prognosis when compared to TP53 wild type and EGFR mutated patients show improved recovery due to availability of the Kinase Inhibitor (KI) treatment. In this study we have observed and concluded that TP53-EGFR co-mutated group also shows promising prognosis for the application of KI treatment. A further large cohort study will establish this clinical observation and enlighten more therapeutically relevant information.

Lung cancer remains a major global health problem because of its high cancer-related mortality rate despite advances in therapeutic approaches. Non-small cell lung cancer (NSCLC), a major subtype of lung cancer, is more amenable to surgical intervention in its early stages. However, the prognosis for advanced NSCLC remains poor, owing to limited treatment options. This underscores the growing need for novel therapeutic strategies to complement existing treatments and improve patient outcomes. In recent years, pentacyclic triterpenoids, a group of natural compounds, have emerged as promising candidates for cancer therapy due to their anticancer properties. Pentacyclic triterpenoids, such as lupeol, betulinic acid, betulin, oleanolic acid, ursolic acid, glycyrrhetinic acid, glycyrrhizin, and asiatic acid, have demonstrated the ability to inhibit cell proliferation and angiogenesis, induce apoptosis, suppress metastasis, and modulate inflammatory and immune pathways in NSCLC cell line models. These compounds exert their effects by modulating important signaling pathways such as NF-κB, PI3K/Akt, and MAPK. Furthermore, advances in drug delivery technologies such as nanocarriers and targeted delivery systems have improved the bioavailability and therapeutic efficacy of triterpenoids. However, despite promising preclinical data, rigorous clinical trials are needed to verify their safety and efficacy. This review explores the role of triterpenoids in NSCLC and therapeutic potential in preclinical models, focusing on their molecular mechanisms of action.

Studies have shown that tumor cell amino acid metabolism is closely associated with lung adenocarcinoma (LUAD) development and progression. However, the comprehensive multi-omics features and clinical impact of the expression of genes associated with amino acid metabolism in the LUAD tumor microenvironment (TME) are yet to be fully understood.

LUAD patients from The Cancer Genome Atlas (TCGA) database were enrolled in the training cohort. Using least absolute shrinkage and selection operator Cox regression analysis, we developed PTAAMG-Sig, a signature based on the expression of tumor-specific amino acid metabolism genes associated with overall survival (OS) prognosis. We evaluated its predictive performance for OS and thoroughly explored the effects of the PTAAMG-Sig risk score on the TME. The risk score was validated in two Gene Expression Omnibus (GEO) cohorts and further investigated against an original cohort of chemotherapy combined with immune checkpoint inhibitors (ICIs). Somatic mutation, chemotherapy response, immunotherapy response, gene set variation, gene set enrichment, immune infiltration, and plasma-free amino acids (PFAAs) profile analyses were performed to identify the underlying multi-omics features.

TCGA datasets based PTAAMG-Sig model consisting of nine genes, KYNU, PSPH, PPAT, MIF, GCLC, ACAD8, TYRP1, ALDH2, and HDC, could effectively stratify the OS in LUAD patients. The two other GEO-independent datasets validated the robust predictive power of PTAAMG-Sig. Our differential analysis of somatic mutations in the high- and low-risk groups in TCGA cohort showed that the TP53 mutation rate was significantly higher in the high-risk group and negatively correlated with OS. Prediction from transcriptome data raised the possibility that PTAAMG-Sig could predict the response to chemotherapy and ICIs therapy. Our immunotherapy cohort confirmed the predictive ability of PTAAMG-Sig in the clinical response to ICIs therapy, which correlated with the infiltration of immune cells (e.g., T lymphocytes and nature killer cells). Corresponding to the concentrations of PFAAs, we discovered that the high PTAAMG-Sig risk score patients showed a significantly lower concentration of plasma-free α-aminobutyric acid.

In patients with LUAD, the PTAAMG-Sig effectively predicted OS, drug sensitivity, and immunotherapy outcomes. These findings are expected to provide new targets and strategies for personalized treatment of LUAD patients.

There remains ongoing debate regarding the association of homologous recombination deficiency (HRD) with patient survival across various malignancies, highlighting the need for a comprehensive understanding of HRD's role in different cancer types. Based on data from databases, we conducted a multivariable omics analysis on HRD in 33 cancer types, focusing mainly on 23 cancers in which HRD was significantly associated with patient overall survival (OS) rates. This analysis included the mechanisms related to patient prognosis, gene expression, gene mutation, and signaling pathways. In this study, HRD was found to be significantly associated with patient prognosis, but its impact varied among different cancers. HRD was linked to different outcomes for patients with distinct tumor subtypes and was correlated with clinical features such as clinical stage and tumor grade. Driver gene mutations, including TP53, MUC4, KRAS, HRAS, FLG, ANK3, BRCA2, ATRX, FGFR3, NFE2L2, MAP3K1, PIK3CA, CIC, FUBP1, ALB, CTNNB1, and MED12, were associated with HRD across specific cancer types. We also analyzed differentially expressed genes (DEGs) and differentially methylated regions (DMRs) in relation to HRD levels in these cancers. Furthermore, we explored the correlation between HRD and signaling pathways, as well as immune cell infiltration. Overall, our findings contribute to a comprehensive understanding of HRD's multifaceted role in cancer.

Study on the prognostic characteristics and biomarkers of lung cancer in Xuanwei Patients.

A retrospective analysis was conducted on the genetic data of 261 NSCLC patients, as well as the prognostic data of 133 patients. The relationship between prognosis and EGFR mutations in the Xuanwei and non Xuanwei cohorts was compared and analyzed.

The superior progression-free survival (PFS) in Xuanwei patients was primarily observed in those with EGFR-mutated tumors (p < 0.05). Further analysis of accompanying mutations and TMB levels revealed an association between high TMB and a favorable prognosis in EGFR-mutated Xuanwei NSCLC.

Xuanwei lung cancer differs from non Xuanwei patients in terms of prognosis and tumor mutation burden, and further research should be conducted.

Prostate cancer, 1 of the most common cancers in men, is influenced by age, genetics, race, and lifestyle. The TP53 gene, encoding the p53 protein crucial for cell cycle regulation and DNA repair, is frequently mutated in metastatic prostate cancers. These mutations impact prognosis and resistance to treatments, underscoring the role of genetic factors in disease progression and therapeutic challenges.

Databases such as PubMed, Scopus, and ISI were searched using the keywords "prostate cancer," "P53," "TP53," "survival," and "prognosis," along with manual searches in other sources. Initial screening and selection of articles were conducted independently and blinded by 2 reviewers, focusing on titles abstracts, and full texts when necessary. The Newcastle-Ottawa Scale (NOS) was used for full-text evaluation. Data were analyzed using STATA 11, with heterogeneity assessed using the I² index.

Overall survival (OS) for prostate cancer patients with TP53 mutations was approximately 13% lower than for those without mutations at 1 year, 20% lower at 3 years, and 16% lower at 5 years. TP53 mutations were also associated with faster disease progression and a 15% reduction in progression-free survival (PFS) over 1 year. The hazard ratio (HR) for death in patients with TP53 mutations was 1.76, and for PFS, it was 1.62, indicating a 76% increased risk of death and a 62% increased risk of disease progression.

TP53 mutations are associated with shorter survival and faster disease progression in prostate cancer, underscoring the importance of precise evaluation and management of these mutations in treatment.

Hypoxia-induced radioresistance limits therapeutic success in cancer. In addition, p53 mutations are widespread in tumors including non-small cell lung carcinomas (NSCLCs), and they might modify the radiation response of hypoxic tumor cells. We therefore analyzed the DNA damage and inflammatory response in chronically hypoxic (1% O2, 48 h) p53 null H358 NSCLC cells after X-ray exposure. We used the colony-forming ability assay to determine cell survival, γH2AX immunofluorescence microscopy to quantify DNA double-strand breaks (DSBs), flow cytometry of DAPI-stained cells to measure cell cycle distribution, ELISAs to quantify IL-6 and IL-8 secretion in cell culture supernatants, and RNA sequencing to determine gene expression. Chronic hypoxia increased the colony-forming ability and radioresistance of H358 cells. It did not affect the formation or resolution of X-ray-induced DSBs. It reduced the fraction of cells undergoing G2 arrest after X-ray exposure and delayed the onset of G2 arrest. Hypoxia led to an earlier enhancement in cytokines secretion rate after X-irradiation compared to normoxic controls. Gene expression changes were most pronounced after the combined exposure to hypoxia and X-rays and pertained to senescence and different cell death pathways. In conclusion, hypoxia-induced radioresistance is present despite the absence of functional p53. This resistance is related to differences in clonogenicity, cell cycle regulation, cytokine secretion, and gene expression under chronic hypoxia, but not to differences in DNA DSB repair kinetics.

Mesenchymal-epithelial transition (MET) exon 14 (METex14) skipping mutation is a rare (3%-4%) driver mutation in non-small cell lung cancer (NSCLC). Tepotinib, a selective MET inhibitor, has shown promise in treating METex14 skipping-mutated NSCLC. However, its feasibility for perioperative application remains unclear. This report describes a 60-year-old man with stage IIIA (cT2N2M0) lung adenocarcinoma harboring a METex14 skipping mutation. After initial treatment with savolitinib was discontinued due to grade 4 transaminitis, the patient was switched to tepotinib, resulting in significant tumor regression. Six months later, further shrinkage was observed, and surgery revealed remarkable pathological response with no residual tumor in lymph nodes (ypT2N0M0, IB). Postoperative tepotinib continued, with no relapse at 6-month follow-up. This case highlights the potential of tepotinib as neoadjuvant therapy for resectable METex14 skipping-mutated NSCLC, warranting further clinical trials.

The aim of this study is to explore the effects and specific mechanisms of heparanase on angiogenesis and iron deficiency anemia in TP53 mutant cancer. For this purpose, we conducted in vitro cell experiments and in vivo animal experiments respectively. In this study, we first analyzed the differential expression of heparanase in TP53 wild-type and mutant cells, and analyzed its effects on iron removal and angiogenesis in two types of CALU-1 and NCI-H358 cells. Secondly, we validated whether the mechanism of action of heparanase on TP53 mutant cells for iron removal and angiogenesis is related to VEGF. We applied the iron removal agonist erastin and VEGF inhibitor bevacizumab in both in vitro and in vivo experiments to validate the relationship between heparanase and VEGF in the mechanisms of iron removal and angiogenesis. The experimental results show that heparanase is highly expressed in TP53 mutated cancer cells, and has anti-ferroptosis and pro-angiogenic effects. Our experiment also confirmed that the effect of heparanase on TP53 mutant cancer's iron removal and angiogenesis is related to VEGF. In short, heparanase is highly expressed in p53 mutated lung cancer, and the mechanism of ferroptosis tolerance to TP53 mutated cancer is related to VEGF.

Using multi-omics data for clustering (cancer subtyping) is crucial for precision medicine research. Despite numerous methods having been proposed, current approaches either do not perform satisfactorily or lack biological interpretability, limiting the practical application of these methods. Based on the biological hypothesis that patients with the same subtype may exhibit similar dysregulated pathways, we developed an Iterative Pathway Fusion approach for enhanced Multi-omics Clustering (IPFMC), a novel multi-omics clustering method involving two data fusion stages. In the first stage, omics data are partitioned at each layer using pathway information, with crucial pathways iteratively selected to represent samples. Ultimately, the representation information from multiple pathways is integrated. In the second stage, similarity network fusion was applied to integrate the representation information from multiple omics. Comparative experiments with nine cancer datasets from The Cancer Genome Atlas (TCGA), involving systematic comparisons with 10 representative methods, reveal that IPFMC outperforms these methods. Additionally, the biological pathways and genes identified by our approach hold biological significance, affirming not only its excellent clustering performance but also its biological interpretability.

The increasing interest in bacteriophage technology has prompted its novel applications to treat different medical conditions, most interestingly cancer. Due to their high specificity, manipulability, nontoxicity, and nanosize nature, phages are promising carriers in targeted therapy and cancer immunotherapy. This approach is particularly timely, as current challenges in cancer research include damage to healthy cells, inefficiency in targeting, obstruction by biological barriers, and drug resistance. Some cancers are being kept at the forefront of phage research, such as colorectal cancer and HCC, while others like lymphoma, cervical cancer, and myeloma have not been retouched in a decade. Common mechanisms are immunogenic antigen display on phage coats and the use of phage as transporters to carry drugs, genes, and other molecules. To date, popular phage treatments being tested are gene therapy and phage-based vaccines using M13 and λ phage, with some vaccines having advanced to human clinical trials. The results from most of these studies have been promising, but limitations in phage-based therapies such as reticuloendothelial system clearance or diffusion inefficiency must be addressed. Before phage-based therapies for cancer can be successfully used in oncology practice, more in-depth research and support from local governments are required.

The tumor suppressor TP53 gene, the most frequently mutated gene in human cancers, produces the product tumor protein p53, which plays an essential role in DNA damage. p53 protein mutations may contribute to tumorigenesis by loss of tumor suppressive functions and malignancy of cancer cells via gain-of-oncogenic functions. We previously reported that mutant p53 proteins form aggregates and that cytoplasmic p53 aggregates were associated with poor prognosis in human ovarian cancer. However, the prognostic impact of p53 aggregation in other tumors including lung squamous cell carcinoma (SCC) is poorly understood. Here, we demonstrated that lung SCC cases with cytoplasmic p53 aggregates had a significantly poor clinical prognosis. Analysis via patient-derived tumor organoids (PDOs) established from lung SCC patients and possessing cytoplasmic p53 aggregates showed that eliminating cytoplasmic p53 aggregates suppressed cell proliferation. RNA sequencing and transcriptome analysis of p53 aggregate-harboring PDOs indicated multiple candidate pathways involved in p53 aggregate oncogenic functions. With lung SCC-derived cell lines, we found that cytoplasmic p53 aggregates contributed to cisplatin resistance. This study thus shows that p53 aggregates are a predictor of poor prognosis in lung SCC and suggests that detecting p53 aggregates via p53 conventional immunohistochemical analysis may aid patient selection for platinum-based therapy.

Recently, the role of inorganic pyrophosphatase 2 (PPA2) has been remaining merely superficial in many tumors. Hence, the aim was to analyze the potential functions of PPA2 in pan-cancer, focusing on its role in breast cancer.

A systematic pan-cancer analysis conducted primarily utilizing various open databases such as TCGA and GTEx. We explored the clinical value of PPA2 as well as various biological functions, including expression levels and subcellular localization, multi-dimensional immune-correlation analysis, co-expression networks, and gene heterogeneity. In addition, we not only verified the function of PPA2 through cell experiments but also analyzed PPA2 at the single-cell level and its drug sensitivity.

PPA2 is abnormally expressed in various tumors, and it is mainly distributed in mitochondria. Furthermore, the indicators (OS, DSS, DFI, and PFI) of analysis hint that PPA2 exhibits significant prognostic value. At the same time, the genomic heterogeneity (including TMB, MSI, MATH, and NEO) of PPA2 in pan-cancer was analyzed. Across multiple tumors, the results showed a close correlation between PPA2 expression levels and different immune signatures (such as immune cell infiltration). All of these indicate that PPA2 could potentially be applied in the guidance of immunotherapy. We also have demonstrated that PPA2 promoted the process of breast cancer. Finally, some potential therapeutic agents (such as Fulvestrant) targeting the abnormal expression of PPA2 are revealed.

In conclusion, the results demonstrated the great value of PPA2 in pan-cancer research, as well as its potential as a therapeutic target for breast tumors.

In invasive lung adenocarcinoma (LUAD), patients with micropapillary (MIP) or solid (SOL) components had a significantly poorer prognosis than those with only lepidic (LEP), acinar (ACI) or papillary (PAP) components. It is interesting to explore the genetic features of different histologic subtypes, especially the highly aggressive components. Based on a cohort of 5,933 patients, this study observed that in different tumor size groups, LUAD with MIP/SOL components showed a different prevalence, and patients with ALK alteration or TP53 mutations had a higher probability of developing MIP/SOL components. To control individual differences, this research used spatial whole-exome sequencing (WES) via laser-capture microdissection of five patients harboring these five coexistent components and identified genetic features among different histologic components of the same tumor. In tracing the evolution of components, we found that titin (TTN) mutation might serve as a crucial intratumor potential driver for MIP/SOL components, which was validated by a cohort of 146 LUAD patients undergoing bulk WES. Functional analysis revealed that TTN mutations enriched the complement and coagulation cascades, which correlated with the pathway of cell adhesion, migration, and proliferation. Collectively, the histologic subtypes of invasive LUAD were genetically different, and certain trunk genotypes might synergize with branching TTN mutation to develop highly aggressive components.

The early detection of lung cancer (LC) improves patient outcomes, but current methods have limitations. Autoantibodies against tumor-associated antigens have potential as early biomarkers. This study evaluated the 9G testTM Cancer/Lung, measuring circulating complexes of two antigen-autoantibody immune complexes (AIC) against their respective free antigens (CYFRA 21-1 and p53) for LC diagnosis. We analyzed 100 LC patients and 119 healthy controls using the 9G testTM Cancer/Lung, quantifying the levels of AICs (CYFRA 21-1-Anti-CYFRA 21-1 autoantibody immune complex (CIC) and p53-Anti-p53 autoantibody immune complex (PIC)), free antigens (CYFRA 21-1 and p53), and ratios of AICs/antigens (LC index). The levels of the CICs and PICs were significantly elevated in LC compared to the controls (p < 0.0062 and p < 0.0026), while free antigens showed no significant difference. The CIC/CYFRA 21-1 and PIC/p53 ratios were also significantly higher in LC (all, p < 0.0001). The LC index, when combining both ratios, exhibited the best diagnostic performance with an area under the curve (AUC) of 0.945, exceeding individual CICs, PICs, and free antigens (AUCs ≤ 0.887). At a cut-off of 3.60, the LC index achieved 81% sensitivity and 95% specificity for LC diagnosis. It detected early-stage (Stage I-II) LC with 87.5% sensitivity, exceeding its performance in advanced stages (72.7%). The LC index showed no significant differences based on age, gender, smoking status (former, current, or never smoker), or pack years smoked. The LC index demonstrates promising potential for early LC diagnosis, exceeding conventional free antigen markers.

Current studies in early cancer detection based on liquid biopsy data often rely on off-the-shelf models and face challenges with heterogeneous data, as well as manually designed data preprocessing pipelines with different parameter settings. To address those challenges, we present AutoCancer, an automated, multimodal, and interpretable transformer-based framework. This framework integrates feature selection, neural architecture search, and hyperparameter optimization into a unified optimization problem with Bayesian optimization. Comprehensive experiments demonstrate that AutoCancer achieves accurate performance in specific cancer types and pan-cancer analysis, outperforming existing methods across three cohorts. We further demonstrated the interpretability of AutoCancer by identifying key gene mutations associated with non-small cell lung cancer to pinpoint crucial factors at different stages and subtypes. The robustness of AutoCancer, coupled with its strong interpretability, underscores its potential for clinical applications in early cancer detection.

Treatment of non-small lung cancer (NSCLC) has evolved in recent years, benefiting from advances in immunotherapy and targeted therapy. However, limited biomarkers exist to assist clinicians and patients in selecting the most effective, personalized treatment strategies. Targeted next-generation sequencing-based genomic profiling has become routine in cancer treatment and generated crucial clinicogenomic data over the last decade. This has made the development of mutational biomarkers for drug response possible.

To investigate the association between a patient's responses to a specific somatic mutation treatment, we analyzed the NSCLC GENIE BPC cohort, which includes 2,004 tumor samples from 1,846 patients.

We identified somatic mutation signatures associated with response to immunotherapy and chemotherapy, including carboplatin-, cisplatin-, pemetrexed- or docetaxel-based chemotherapy. The prediction power of the chemotherapy-associated signature was significantly affected by epidermal growth factor receptor (EGFR) mutation status. Therefore, we developed an EGFR wild-type-specific mutation signature for chemotherapy selection.

Our treatment-specific gene signatures will assist clinicians and patients in selecting from multiple treatment options.

The TP53 gene is renowned as a tumor suppressor, playing a pivotal role in overseeing the cell cycle, apoptosis, and maintaining genomic stability. Dysregulation of p53 often contributes to the initiation and progression of various cancers, including lung cancer (LC) subtypes. The review explores the intricate relationship between p53 and its role in the development and progression of LC. p53, a crucial tumor suppressor protein, exists in various isoforms, and understanding their distinct functions in LC is essential for advancing our knowledge of this deadly disease. This review aims to provide a comprehensive literature overview of p53, its relevance to LC, and potential clinical applications.

Lung cancer, recognized globally as a leading cause of malignancy-associated morbidity and mortality, is marked by its high prevalence and lethality, garnering extensive attention within the medical community. Mitophagy is a critical cellular process that plays a crucial role in regulating metabolism and ensuring quality control within cells. Its relevance to lung cancer has garnered significant attention among researchers and scientists. Mitophagy's involvement in lung cancer encompasses its initiation, progression, metastatic dissemination and treatment. The regulatory landscape of mitophagy is complex, involving numerous signaling proteins and pathways that may exhibit aberrant alterations or mutations within the tumor environment. In the field of treatment, the regulation of mitophagy is considered key to determining cancer chemotherapy, radiation therapy, other treatment options, and drug resistance. Contemporary investigations are directed towards harnessing mitophagy modulators, both inhibitors and activators, in therapeutic strategies, with an emphasis on achieving specificity to minimize collateral damage to healthy cellular populations. Furthermore, molecular constituents and pathways affiliated with mitophagy, serving as potential biomarkers, offer promising avenues for enhancing diagnostic accuracy, prognostic assessment, and prediction of therapeutic responses in lung cancer. Future endeavors will also involve investigating the impact of mitophagy on the composition and function of immune cells within the tumor microenvironment, aiming to enhance our understanding of how mitophagy modulates the immune response to lung cancer. This review aims to comprehensively overview recent advancements about the role of mitophagy in the tumor genesis, progenesis and metastasis, and the impact of mitophagy on the treatment of lung cancer. We also discussed the future research direction of mitophagy in the field of lung cancer.

Lung adenocarcinoma (LUAD) is the most common type of lung cancer and is characterized by a high death rate and a poor prospect for survival. Anoikis, which is a kind of programmed cell apoptosis, is an important factor in the advancement of tumors. Nonetheless, the function of anoikis-related lncRNAs (ARLRs) in LUAD is still not well understood. The TCGA database was queried for genomic and clinical information. A prognostic signature for ARLRs was established via the use of coexpression analysis and Cox regression. Validation of the model's accuracy was conducted utilizing K-M curves and receiver operating characteristic (ROC) curves, and the signature was utilized to develop a nomogram. LncRNAs were implicated in the progression of tumors, as determined by functional enrichment analysis. There was an improvement in prognosis, increased immune cell infiltration, and higher immune scores among the low-risk patients. Additionally, we found that the two groups had varied anticancer drug sensitivities, which could help guide treatment. The impact of one ARLR, AC026355.2, on migration and invasion was validated by in vitro experiments in LUAD cells. Herein, a new lncRNA signature associated with anoikis was identified and estimated, potentially serving as a prognostic indicator for LUAD patients.

In the current work, the synergy between natural compounds and conventional chemotherapeutic drugs is comprehensively reviewed in light of current preclinical research findings. The prognosis for lung cancer patients is poor, with a 5-year survival rate of 18.1%. The use of natural compounds in combination with conventional chemotherapeutic drugs has gained significant attention as a potential novel approach in the treatment of lung cancer. The present work highlights the importance of finding more effective therapies to increase survival rates. Chemotherapy is a primary treatment option for lung cancer but it has limitations such as reduced effectiveness because cancer cells become resistant. Natural compounds isolated from medicinal plants have shown promising anticancer or chemopreventive properties and their synergistic effect has been observed when combined with conventional therapies. The combined use of an anti-cancer drug and a natural compound exhibits synergistic effects, enhancing overall therapeutic actions against cancer cells. In conclusion, this work provides an overview of the latest preclinical research on medicinal plants and plant-derived compounds as alternative or complementary treatment options for lung cancer chemotherapy and discusses the potential of natural compounds in treating lung cancer with minimal side effects.

The efficacy of radiotherapy, a cornerstone in the treatment of lung adenocarcinoma (LUAD), is profoundly undermined by radiotolerance. This resistance not only poses a significant clinical challenge but also compromises patient survival rates. Therefore, it is important to explore this mechanism for the treatment of LUAD. Multiple public databases were used for single-cell RNA sequencing (scRNA-seq) data. We filtered, normalized and downscaled scRNA-seq data based on the Seurat package to obtain different cell subpopulations. Subsequently, the ssGSEA algorithm was used to assess the enrichment scores of the different cell subpopulations, and thus screen the cell subpopulations that are most relevant to radiotherapy tolerance based on the Pearson method. Finally, pseudotime analysis was performed, and a preliminary exploration of gene mutations in different cell subpopulations was performed. We identified HIST1H1D+ A549 and PIF1+ A549 as the cell subpopulations related to radiotolerance. The expression levels of cell cycle-related genes and pathway enrichment scores of these two cell subpopulations increased gradually with the extension of radiation treatment time. Finally, we found that the proportion of TP53 mutations in patients who had received radiotherapy was significantly higher than that in patients who had not received radiotherapy. We identified two cellular subpopulations associated with radiotherapy tolerance, which may shed light on the molecular mechanisms of radiotherapy tolerance in LUAD and provide new clinical perspectives.