Somatic mutations affect key pathways in lung adenocarcinoma

Insights into targeting LKB1 in tumorigenesis

Genetic alterations to serine-threonine kinase 11 (STK11) have been implicated in Peutz-Jeghers syndrome and tumorigenesis. Further exploration of the context-specific roles of liver kinase B1 (LKB1; encoded by STK11) observed that it regulates AMP-activated protein kinase (AMPK) and AMPK-related kinases. Given that both migration and proliferation are enhanced with the loss of LKB1 activity combined with the prevalence of STK11 genetic alterations in cancer biopsies, LKB1 was marked as a tumor suppressor. However, the role of LKB1 in tumorigenesis is paradoxical as LKB1 activates autophagy and reactive oxygen species scavenging while dampening anoikis, which contribute to cancer cell survival. Due to the pro-tumorigenic properties of LKB1, targeting LKB1 pathways is now relevant for cancer treatment. With the recent successes of targeting LKB1 signaling in research and clinical settings, and enhanced cytotoxicity of chemical compounds in LKB1-deficient tumors, there is now a need for LKB1 inhibitors. However, validating LKB1 inhibitors is challenging as LKB1 adaptor proteins, nucleocytoplasmic shuttling, and splice variants all manipulate LKB1 activity. Furthermore, STE-20-related kinase adaptor protein (STRAD) and mouse protein 25 dictate LKB1 cellular localization and kinase activity. For these reasons, prior to assessing the efficacy and potency of pharmacological candidates, the functional status of LKB1 needs to be defined. Therefore, to improve the understanding of LKB1 in physiology and oncology, this review highlights the role of LKB1 in tumorigenesis and addresses the therapeutic relevancy of LKB1 inhibitors.

Pan-cancer analysis of biallelic inactivation in tumor suppressor genes identifies KEAP1 zygosity as a predictive biomarker in lung cancer

The canonical model of tumor suppressor gene (TSG)-mediated oncogenesis posits that loss of both alleles is necessary for inactivation. Here, through allele-specific analysis of sequencing data from 48,179 cancer patients, we define the prevalence, selective pressure for, and functional consequences of biallelic inactivation across TSGs. TSGs largely assort into distinct classes associated with either pan-cancer (Class 1) or lineage-specific (Class 2) patterns of selection for biallelic loss, although some TSGs are predominantly monoallelically inactivated (Class 3/4). We demonstrate that selection for biallelic inactivation can be utilized to identify driver genes in non-canonical contexts, including among variants of unknown significance (VUSs) of several TSGs such as KEAP1. Genomic, functional, and clinical data collectively indicate that KEAP1 VUSs phenocopy established KEAP1 oncogenic alleles and that zygosity, rather than variant classification, is predictive of therapeutic response. TSG zygosity is therefore a fundamental determinant of disease etiology and therapeutic sensitivity.

Multi-Omics Analysis Reveals Immune Infiltration and Clinical Significance of Phosphorylation Modification Enzymes in Lung Adenocarcinoma

Protein phosphorylation is a dynamic and reversible modification involved in almost all cellular processes. Numerous investigations have shown that protein phosphorylation modification enzymes (PPMEs) that regulate protein phosphorylation play an important role in the occurrence and treatment of tumors. However, there is still a lack of effective insights into the value of PPMEs in the classification and treatment of patients with lung adenocarcinoma (LUAD). Here, four topological algorithms identified 15 hub PPMEs from a protein-protein interaction (PPI) network. This PPI network was constructed using 124 PPMEs significantly correlated with 35 cancer hallmark-related pathways. Our study illustrates that these hub PPMEs can affect the survival of patients with LUAD in the form of somatic mutation or expression perturbation. Consistency clustering based on hub PPMEs recognized two phosphorylation modification subtypes (namely cluster1 and cluster2) from LUAD. Compared with patients in cluster1, the survival prognosis of patients in cluster2 is worse. This disparity is probably attributed to the higher tumor mutation burden, the higher male proportion, and the more significant expression disturbance in patients in cluster2. Moreover, phosphorylation modification subtypes also have different characteristics in terms of immune activity, immune infiltration level, immunotherapy response, and drug sensitivity. We constructed a PSig scoring system by using a principal component analysis algorithm to estimate the level of phosphorylation modification in individual LUAD patients. Patients in the high and low PSig score groups demonstrated different characteristics in terms of survival rate, tumor mutation burden, somatic gene mutation rate, immune cell abundance, and sensitivity to immunotherapy and drug treatment. This work reveals that phosphorylation plays a non-negligible role in the tumor microenvironment and immunotherapy of LUAD. Evaluating the phosphorylation status of individual LUAD patients by the PSig score can contribute to enhancing our cognition of the tumor microenvironment and guiding the formulation of more effective personalized treatment strategies.

Ensemble machine learning models for lung cancer incidence risk prediction in the elderly: a retrospective longitudinal study

BACKGROUND

Identifying high risk factors and predicting lung cancer incidence risk are essential to prevention and intervention of lung cancer for the elderly. We aim to develop lung cancer incidence risk prediction model in the elderly to facilitate early intervention and prevention of lung cancer.

METHODS

We stratified the population into six subgroups according to age and gender. For each subgroup, random forest, extreme gradient boosting, deep neural networks, support vector machine, multiple logistic regression and deep Q network (DQN) models were developed and validated. Models were trained and tested using samples from 2000 to 2015 and independent external validated through those from 2016 to 2019. The suitable model for lung cancer risk prediction and high risk factors identification was chosen based on internal validation and independent external validation.

RESULTS

The DQN model achieved the optimal prediction performance in stratified subgroups, with AUROC ranging from 0.937 to 0.953, recall ranging from 0.932 to 0.943, F2-score ranging from 0.929 to 0.946, precision ranging from 0.926 to 0.952, F1-score ranging from 0.933 to 0.963 and RMSE ranging from 0.21 to 0.27. SHAP values were supplied for model interpretability. High risk factors of lung cancer incidence were identified in the elderly. Men ≥ 65 carrying C > A/G > T mutation had the highest lung cancer incidence decrease of 39.5% after five years quitting in stratified elderly groups, which were 1.83 times more than women ≥ 65 not carrying C > A/G > T mutation.

CONCLUSIONS

The DQN model may be suitable for identifying high risk factors and predicting lung cancer risk with high performance. The proposed intervention and diagnosis pathways could be used for early screening and intervention before the occurrence of lung cancer, which could help oncologists develop targeted intervention strategies for the stratified elderly to reduce lung cancer incidence and improve therapeutic effect. Proposed method could also be used in predicting the risk of other chronic diseases to help conduct intervention and reduce incidence.

Identification of cancer driver genes based on hierarchical weak consensus model

Cancer is a complex gene mutation disease that derives from the accumulation of mutations during somatic cell evolution. With the advent of high-throughput technology, a large amount of omics data has been generated, and how to find cancer-related driver genes from a large number of omics data is a challenge. In the early stage, the researchers developed many frequency-based driver genes identification methods, but they could not identify driver genes with low mutation rates well. Afterwards, researchers developed network-based methods by fusing multi-omics data, but they rarely considered the connection among features. In this paper, after analyzing a large number of methods for integrating multi-omics data, a hierarchical weak consensus model for fusing multiple features is proposed according to the connection among features. By analyzing the connection between PPI network and co-mutation hypergraph network, this paper firstly proposes a new topological feature, called co-mutation clustering coefficient (CMCC). Then, a hierarchical weak consensus model is used to integrate CMCC, mRNA and miRNA differential expression scores, and a new driver genes identification method HWC is proposed. In this paper, the HWC method and current 7 state-of-the-art methods are compared on three types of cancers. The comparison results show that HWC has the best identification performance in statistical evaluation index, functional consistency and the partial area under ROC curve.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13755-024-00279-6.

Real-World Survival Outcomes in Non-Small Cell Lung Cancer: The Impact of Genomic Testing and Targeted Therapies in a Latin American Middle-Income Country

PURPOSE

Targeted therapies are indicated for patients with non-small cell lung cancer (NSCLC) and driver tumor mutations. However, real-world studies on the survival benefits of these agents are limited. This study aimed to evaluate the effect of targeted therapies matched to a genomic alteration on the survival of patients with NSCLC.

METHODS

This retrospective study included 446 patients with advanced NSCLC who underwent next-generation sequencing between 2016 and 2023 at the Instituto Nacional de Cancerología in Mexico. The primary outcomes were progression-free survival (PFS) and overall survival (OS).

RESULTS

For the entire cohort, the PFS and OS were 10.71 months (95% CI, 9.35 to 12.06) and 47.77 months (95% CI, 29.67 to 65.86). PFS was significantly longer in patients with actionable mutations treated with targeted therapies (19.41 months [95% CI, 14.27 to 24.55]; P < .001) than in patients without actionable mutations (6.4 months [95% CI, 4.4 to 8.4]) or not treated with targeted therapies (6.6 months [95% CI, 5.3 to 7.89]). Similarly, OS was significantly longer in patients with actionable mutations treated with targeted therapies (89.69 months [95% CI, 45.54 to 133.84]; P < .001) than in patients without actionable mutations (17.11 months [95% CI, 8.65 to 25.57]) or not treated with targeted therapies (22.3 months [95% CI, 12.48 to 32.1]). Survival gains were driven by significant improvements in PFS and OS in patients with EGFR and ALK mutations.

CONCLUSION

This real-world data analysis demonstrated that targeted therapies improve the survival of patients with NSCLC with actionable mutations, which supports a recommendation for widening access to broad-based genomic testing and targeted therapies.

RB1 Mutations Induce Smoking-Related Bladder Cancer by Modulating the Cytochrome P450 Pathway

Cigarette smoking causes multiple cancers by directly influencing mutation burden of driver mutations. However, the mechanism between somatic mutation caused by cigarette smoking and bladder tumorigenesis remains elusive. Smoking-related mutation profile of bladder cancer was characterized by The Cancer Genome Atlas cohort. Integraticve OncoGenomics database was utilized to detect the smoking-related driver genes, and its biological mechanism predictions were interpreted based on bulk transcriptome and single-cell transcriptome, as well as cell experiments. Cigarette smoking was associated with an increased tumor mutational burden under 65 years old (p = 0.031), and generated specific mutational signatures in smokers. RB1 was identified as a differentially mutated driver gene between smokers and nonsmokers, and the mutation rate of RB1 increased twofold after smoking (p = 0.008). RB1 mutations and the 4-aminobiphenyl interference could significantly decrease the RB1 expression level and thus promote the proliferation, invasion, and migration ability of bladder cancer cells. Enrichment analysis and real-time quantitative PCR (RT-qPCR) data showed that RB1 mutations inhibited cytochrome P450 pathway by reducing expression levels of UGT1A6 and AKR1C2. In addition, we also observed that the component of immunological cells was regulated by RB1 mutations through the stronger cell-to-cell interactions between epithelial scissor+ cells and immune cells in smokers. This study highlighted that RB1 mutations could drive smoking-related bladder tumorigenesis through inhibiting cytochrome P450 pathway and regulating tumor immune microenvironment.

Revolutionizing prognostic predictions in colorectal cancer: Macrophage‑driven transcriptional insights from single‑cell RNA sequencing and gene co‑expression network analysis

Tumor-associated macrophages have become important biomarkers for cancer diagnosis, prognosis and therapy. The dynamic changes in macrophage subpopulations significantly impact the outcomes of cancer immunotherapy. Hence, identifying additional macrophage-related biomarkers is essential for enhancing prognostic predictions in colorectal cancer (CRC) immunotherapy. CRC single-cell RNA sequencing (scRNA-seq) data was obtained from the Gene Expression Omnibus (GEO) database. The data were processed, normalized and clustered using the 'Seurat' package. Cell types within each cluster were annotated using the 'SingleR' package. Weighted gene co-expression network analysis identified modules corresponding to specific cell types. A non-negative matrix factorization algorithm was employed to segregate different clusters based on the selected module. Differentially expressed genes (DEGs) were identified across various clusters and a prognostic model was constructed using lasso regression and Cox regression analyses. The robustness of the model was validated using The Cancer Genome Atlas (TCGA) database and GEO microarrays. Additionally, the prognosis, immune characteristics and response to immune checkpoint inhibitor (ICI) therapy were individually analyzed. The scRNA-seq data from GSE200997, consisting of 23 samples, were analyzed. Dimensionality reduction and cluster identification allowed the isolation of the primary myeloid cell subpopulations. The macrophage-related brown module was identified, which was further divided into two clusters. Using the DEGs from these clusters, a prognostic model was developed, comprising five macrophage-related genes. The robustness of the model was confirmed using microarray datasets GSE17536, GSE38832 and GSE39582, as well as TCGA cohort. Patients classified as high-risk by the present model exhibited poorer survival rates, lower tumor mutation burden, reduced microsatellite instability, lower tumor purity, more severe tumor immune dysfunction and exclusion, and less benefit from ICIs therapy compared with low-risk patients. The present prognostic model shows promise as a biomarker for risk stratification and predicting therapeutic efficacy in patients with CRC. However, further well-designed prospective studies are necessary to validate the findings.

LRP1B Suppresses Immunotherapy Efficacy in Lung Adenocarcinoma by Preventing Ferroptosis

BACKGROUND

Immune biomarkers for non-small-cell lung cancer (NSCLC) are programmed death ligand 1 (PD-L1) and tumor mutational burden (TMB). However, they cannot accurately predict the effectiveness of immunotherapy. Identifying appropriate biomarkers that can differentiate between beneficiary groups is imperative.

METHODS

We identified lipoprotein receptor-related protein 1B (LRP1B) mutation as a potential biomarker for immunotherapy by analyzing clinical data, combined with bioinformatics analysis. The effects of LRP1B on ferroptosis were assessed using qRT-PCR, Western blotting, CCK-8 assay, and flow cytometry. The potential mechanism underlying the regulation of ferroptosis by LRP1B was elucidated using qRT-PCR, Western blotting, ChIP, and dual-luciferase reporter gene assays.

RESULTS

Through the collection and analysis of clinical data, we had established that LRP1B mutations are closely associated with immunotherapy. Bioinformatics analysis revealed significant differences in the expression levels of PD-L1 and TMB between patients with LRP1B mutation and wild-type patients in lung adenocarcinoma (LUAD). Furthermore, we observed that patients with LRP1B mutation in LUAD had significantly higher levels of tumor-infiltrating lymphocytes (TILs) than wild-type patients. In addition, we found that patients with LRP1B mutation in LUAD had significantly prolonged progression-free survival (PFS) compared to wild-type patients. However, the differences of PD-L1 expression, TILs, and PFS were not observed in patients with LRP1B mutation in lung squamous cell carcinoma (LUSC). These findings provided strong evidence that LRP1B mutation was a potential biomarker for immunotherapy in LUAD. Moreover, our in vivo experiments indicated that knockdown of LRP1B enhanced the efficacy of mPD-1, and mechanistic studies revealed that LRP1B regulated the sensitivity of cells to ferroptosis by modulating the expression of SLC7A11 through altering the phosphorylation level of STAT3. Further analysis revealed that LRP1B knockdown promoted immunotherapy in vivo.

CONCLUSIONS

Our results confirmed that LRP1B affected the efficacy of immunotherapy by modulating the sensitivity of NSCLC cells to ferroptosis. LRP1B mutations represent a highly promising immunotherapeutic biomarker for NSCLC.

KMT2A facilitates the epithelial-to-mesenchymal transition and the progression of ovarian cancer

Epithelial-mesenchymal transition (EMT) plays critical roles in cancer progression and metastasis. Thus, the exploration of the molecular mechanism regulating EMT would provide potential opportunities for the therapy of metastatic ovarian cancer (OC). Herein, we investigated the putative role of KMT2A in modulating EMT and metastasis in OC. The expression of KMT2A in OC was detected by Western blot and immunohistochemistry and its relationship with clinicopathological factors was analyzed. The effect of KMT2A on the biological behavior of OC cells was examined. Moreover, the expressions of EMT-associated proteins were detected in vivo and vitro by Western blot, immunofluorescence, and immunohistochemistry. KMT2A was highly expressed in OC cell lines and tissues and was positively correlated with advanced International Federation of Gynecology and Obstetrics (FIGO) stage, pathological grade, and metastasis. KMT2A overexpression was correlated with poor prognosis. Suppression of KMT2A inhibited OC cells proliferation, migration, and invasion and induced their apoptosis in vitro and vivo. In contrast, the ectopic expression of KMT2A had the opposite effects. Furthermore, KMT2A knockdown inhibited TGF-β-induced EMT in OC and reduced the phosphorylation levels of Smad2. Taken together, these observations demonstrate that KMT2A could promote the malignant behavior of OC by activating TGF-β/Smad signaling pathway and may be a potential prognostic biomarker and therapeutic target for OC.

Identification of Cancer Driver Genes based on Dynamic Incentive Model

Cancer is a complex genomic mutation disease, and identifying cancer driver genes promotes the development of targeted drugs and personalized therapies. The current computational method takes less consideration of the relationship among features and the effect of noise in protein-protein interaction(PPI) data, resulting in a low recognition rate. In this paper, we propose a cancer driver genes identification method based on dynamic incentive model, DIM. This method firstly constructs a hypergraph to reduce the impact of false positive data in PPI. Then, the importance of genes in each hyperedge in hypergraph is considered from three perspectives, network and functional score(NFS) is proposed. By analyzing the relation among features, the dynamic incentive model is proposed to fuse NFS, the differential expression score of mRNA and the differential expression score of miRNA. DIM is compared with some classical methods on breast cancer, lung cancer, prostate cancer, and pan-cancer datasets. The results show that DIM has the best performance on statistical evaluation indicators, functional consistency and the partial area under the ROC curve, and has good cross-cancer capability.

Primary hepatoid adenocarcinoma of the lung in patient with silicosis: a case report and literature review

Introduction

Hepatoid adenocarcinoma of the lung (HAL) is a special type of adenocarcinoma originating from the lung with adenoid- and hepatocyte-like differentiation. HAL is rare in clinical practice. Here, we present the case of a patient with HAL.

Case presentation

A 59-year-old man was admitted to the hospital 4 days because of lung mas observed. Chest computed tomography (CT) revealed a lobulated mass shadow in the right lower lobe, approximately 3.5 × 3.3 cm in size. CT-guided percutaneous biopsy of the right lower lung was performed. The pathological results indicated a moderately to poorly differentiated adenocarcinoma. The patient underwent thoracoscopic right middle and lower lobectomy and systematic lymph node dissection. The postoperative pathology was primary HAL, with the staging of T2bN2M0 (stage III A). Recurrence-free survival and overall survival were 6 and 19 months, respectively Preoperatively, the level of alpha-fetoprotein was negative; however, after recurrence, it increased to 87.8.

Conclusion

Pulmonary hepatoid adenocarcinoma is a rare subtype of malignant lung tumor, combined silicosis is more rare. Early surgical intervention can benefit patients in the early stages of the disease, whereas chemotherapy remains the main systemic treatment modality for postoperative and advanced stages. With the increasing popularity of genetic testing, it is important to focus on improving genetic examination.

Non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is one of the most frequent cancer types and is responsible for the majority of cancer-related deaths worldwide. The management of NSCLC has improved considerably, especially in the past 10 years. The systematic screening of populations at risk with low-dose CT, the implementation of novel surgical and radiotherapeutic techniques and a deeper biological understanding of NSCLC that has led to innovative systemic treatment options have improved the prognosis of patients with NSCLC. In non-metastatic NSCLC, the combination of various perioperative strategies and adjuvant immunotherapy in locally advanced disease seem to enhance cure rates. In metastatic NSCLC, the implementation of novel drugs might prolong disease control together with preserving quality of life. The further development of predictive clinical and genetic markers will be essential for the next steps in individualized treatment concepts.

Mitochondrial VDAC1 Silencing in Urethane-Induced Lung Cancer Inhibits Tumor Growth and Alters Cancer Oncogenic Properties

Alterations in cellular metabolism are vital for cancer cell growth and motility. Here, we focused on metabolic reprogramming and changes in tumor hallmarks in lung cancer by silencing the expression of the mitochondrial gatekeeper VDAC1. To better mimic the clinical situation of lung cancer, we induced lung cancer in A/J mice using the carcinogen urethane and examined the effectiveness of si-m/hVDAC1-B encapsulated in PLGA-PEI nanoparticles. si-m/hVDAC1-B, given intravenously, induced metabolism reprogramming and inhibited tumor growth as monitored using MRI. Mice treated with non-targeted (NT) PLGA-PEI-si-NT showed many large size tumors in the lungs, while in PLGA-PEI-si-m/hVDAC-B-treated mice, lung tumor number and area were markedly decreased. Immunofluorescence staining showed decreased expression of VDAC1 and metabolism-related proteins and altered expression of cancer stem cell markers. Morphological analysis showed two types of tumors differing in their morphology; cell size and organization within the tumor. Based on specific markers, the two tumor types were identified as small cell (SCLC) and non-small cell (NSCLC) lung cancer. These two types of tumors were found only in control tumors, suggesting that PLGA-PEI-si-m/hVDAC1-B also targeted SCLC. Indeed, using a xenograft mouse model of human-derived SCLC H69 cells, si-m/hVDAC1-B inhibited tumor growth and reduced the expression of VDAC1 and energy- and metabolism-related enzymes, and of cancer stem cells in the established xenograft. Additionally, intravenous treatment of urethane-induced lung cancer mice with the VDAC1-based peptide, Retro-Tf-D-LP4, showed inhibition of tumor growth, and decreased expression levels of metabolism- and cancer stem cells-related proteins. Thus, silencing VDAC1 targeting both NSCLC and SCLC points to si-VDAC1 as a possible therapeutic tool to treat these lung cancer types. This is important as target NSCLC tumors undergo transformation to SCLC.

KRASG12C Inhibitors in Non-Small Cell Lung Cancer: A Review

Rat sarcoma virus (RAS) GTPase is one of the most important drivers of non-small cell lung cancer (NSCLC). RAS has three different isoforms (Harvey rat sarcoma viral oncogene homolog [HRAS], Kirsten rat sarcoma viral oncogene homolog [KRAS] and Neuroblastoma ras viral oncogene homolog [NRAS]), of which KRAS is most commonly mutated in NSCLC. The mutated KRAS protein was historically thought to be "undruggable" until the development of KRASG12C inhibitors. In this review, from the aspect of brain metastasis, we aim to provide an overview of the advances in therapies that target KRASG12C, the limitations of the current treatments, and future prospects in patients with KRAS p.G12C mutant NSCLC.

Therapeutic advances of targeting receptor tyrosine kinases in cancer

Receptor tyrosine kinases (RTKs), a category of transmembrane receptors, have gained significant clinical attention in oncology due to their central role in cancer pathogenesis. Genetic alterations, including mutations, amplifications, and overexpression of certain RTKs, are critical in creating environments conducive to tumor development. Following their discovery, extensive research has revealed how RTK dysregulation contributes to oncogenesis, with many cancer subtypes showing dependency on aberrant RTK signaling for their proliferation, survival and progression. These findings paved the way for targeted therapies that aim to inhibit crucial biological pathways in cancer. As a result, RTKs have emerged as primary targets in anticancer therapeutic development. Over the past two decades, this has led to the synthesis and clinical validation of numerous small molecule tyrosine kinase inhibitors (TKIs), now effectively utilized in treating various cancer types. In this manuscript we aim to provide a comprehensive understanding of the RTKs in the context of cancer. We explored the various alterations and overexpression of specific receptors across different malignancies, with special attention dedicated to the examination of current RTK inhibitors, highlighting their role as potential targeted therapies. By integrating the latest research findings and clinical evidence, we seek to elucidate the pivotal role of RTKs in cancer biology and the therapeutic efficacy of RTK inhibition with promising treatment outcomes.

Nono induces Gadd45b to mediate DNA repair

RNA-binding proteins are frequently deregulated in cancer and emerge as effectors of the DNA damage response (DDR). The non-POU domain-containing octamer-binding protein NONO/p54nrb is a multifunctional RNA-binding protein that not only modulates the production and processing of mRNA, but also promotes the repair of DNA double-strand breaks (DSBs). Here, we investigate the impact of Nono deletion in the murine KP (KRas G12D , Trp53 -/- ) cell-based lung cancer model. We show that the deletion of Nono impairs the response to DNA damage induced by the topoisomerase II inhibitor etoposide or the radiomimetic drug bleomycin. Nono-deficient KP (KPN) cells display hyperactivation of DSB signalling and high levels of DSBs. The defects in the DDR are accompanied by reduced RNA polymerase II promoter occupancy, impaired nascent RNA synthesis, and attenuated induction of the DDR factor growth arrest and DNA damage-inducible beta (Gadd45b). Our data characterise Gadd45b as a putative Nono-dependent effector of the DDR and suggest that Nono mediates a genome-protective crosstalk of the DDR with the RNA metabolism via induction of Gadd45b.

Therapeutic and prognostic effect of disulfidptosis-related genes in lung adenocarcinoma

Disulfidptosis, a new form of cell death, may be induced by disulfide stress associated with cystine disulfide buildup, which can promote cell toxicity, leading to cell death. Nevertheless, the role of direct prognosis and the mechanism underlying the regulation of disulfidptosis-related genes (DRGs) in lung adenocarcinoma (LUAD) are still unknown. This study aimed to investigate the role of DRGs in LUAD prognosis and diagnosis through multiomics analysis. First, copy number variations (CNVs) and mutations in the 10 genes were assessed. Considering that five differentially expressed genes (DEGs) were associated with disulfidptosis, a novel DRG score that can be utilized to anticipate LUAD prognosis was developed. Next, the generated receiver operating characteristic (ROC) and survival curves demonstrated that the model had an excellent predictive quality in LUAD in both the training and validation cohorts. Meanwhile, substantial functional disparities between the high DRG group and the low DRG group were observed, and the second gap mitosis (G2M) checkpoint, E2 promoter-binding factor (E2F) targets, and myelocytomatosis (MYC) target activities were consistently higher in the high DRG group than in the low DRG group. Additionally, the T-cell dysfunction score and tumor inflammation signature (Merck18) were negatively correlated with DRGs, whereas myeloid-derived suppressor cells (MDSCs) were positively correlated with DRGs. Moreover, DRGs were negatively linked to most of the immunological checkpoints. Meanwhile, samples of low DRGs benefited more from immune checkpoint blockade (ICB). The correlation analysis between DRGs and clinical characteristics revealed increasing malignancy with increasing DRG scores. Drug sensitization experiment results indicated that sensitivity to cisplatin, vincristine, docetaxel, and gemcitabine was higher in the high DRG group than in the low DRG group. The function of model genes in LUAD was also verified using immunohistochemistry, quantitative reverse transcription-polymerase chain reaction (qRT-PCR), western blotting, 5-ethynyl-2'-deoxyuridine (EDU), and clonogenic formation.

A genomic instability-associated lncRNA signature for predicting prognosis and biomarkers in lung adenocarcinoma

Genomic instability (GI) was associated with tumorigenesis. However, GI-related lncRNA signature (GILncSig) in lung adenocarcinoma (LUAD) is still unknown. In this study, the lncRNA expression data, somatic mutation information and clinical survival information of LUAD were downloaded from The Cancer Genome Atlas (TCGA) and performed differential analysis. Functional and prognosis analysis revealed that multiple GI-related pathways were enriched. By using univariate and multivariate Cox regression analysis, 5 GI-associated lncRNAs (AC012085.2, FAM83A-AS1, MIR223HG, MIR193BHG, LINC01116) were identified and used to construct a GILncSig model. Mutation burden analysis indicated that the high-risk GI group had much higher somatic mutation count and the risk score constructed by the 5 GI-associated lncRNAs was an independent predictor for overall survival (OS) (P < 0.05). Overall, our study provides valuable insights into the involvement of GI-associated lncRNAs in LUAD and highlights their potential as therapeutic targets.

Giant Myxofibrosarcoma in the Lower Limb: An Overview of Diagnostic and Clinical Management

Myxofibrosarcoma (MFS), an aggressive soft tissue sarcoma, is one of the undifferentiated pleomorphic sarcomas; it has a low incidence, affecting people in the sixth to eighth decades of life. It usually involves the extremities and is painless with a slow-growing pattern. Based on the case of a 52-year-old female patient who presented with a painful, massive, rapid-growing, ulcerated tumor of the anterior surface of the left thigh, we performed a literature review regarding the current standard of care for patients with MFS. Computed tomography examination, followed by magnetic resonance imaging and surgical biopsy with histopathological examination, confirmed the diagnosis and the presence of lung and inguinal lymph node metastases. Due to the rapid-growing pattern and the local aggressiveness, our tumor board team recommended emergency excisional surgery, with subsequent reconstructive procedures followed by referral to an oncological center. This review emphasizes the importance of proper and rapid diagnosis, followed by multidisciplinary management, for MFS cases with atypical presentation and distal metastases to improve overall outcomes.

Genomic Alterations Correlated to Trastuzumab Resistance and Clinical Outcomes in HER2+/HR- Breast Cancers of Patients Living in Northwestern China

Anti-HER2 therapy has significantly improved the survival rates of patients with HER2+ breast cancer. However, a subset of these patients eventually experience treatment failure, and the underlying genetic mechanisms remain largely unexplored. This underscores the need to investigate the genomic heterogeneity of HER2+ breast cancer. In this study, we focus on HER2+/HR- breast cancer, as it differs from HER2+/HR+ breast cancer in terms of genetic and biological characteristics. We performed gene-targeted genome sequencing on 45 HER2+/HR- breast cancer samples and identified 650 mutations across 268 cancer-related genes. TP53 (71.1%) and PIK3CA (35.6%) were the most frequently mutated genes in our sample. Additionally, ERBB2 (77.8%), CDK12 (42.2%), and MYC (11.1%) exhibited a high frequency of copy number amplifications (CNAs). Comparative analysis with two other HER2+/HR- breast cancer cohorts revealed that our cohort had higher genetic variation rates in ARID1A, PKHD1, PTPN13, FANCA, SETD2, BRCA2, BLM, STAG2, FAT1, TOP2A, POLE, ATM, KMT2B, FGFR4, and EPAS1. Notably, in our cohort, NF1 and ATM mutations were more prevalent in trastuzumab-resistant patients (NF1, p=0.016; ATM, p=0.006) and were associated with primary trastuzumab resistance (NF1, p=0.042; ATM, p=0.021). Moreover, patients with NF1 mutations (p=0.009) and high histological grades (p=0.028) were more likely to experience early relapse. Ultimately, we identified a unique cancer-related gene mutation profile and a subset of genes associated with primary resistance to trastuzumab and RFS in patients with HER2+/HR- breast cancer in Northwest China. These findings could lay the groundwork for future studies aimed at elucidating the mechanisms of resistance to trastuzumab and improving HER2-targeted treatment strategies.

TMPRSS2 is a tumor suppressor and its downregulation promotes antitumor immunity and immunotherapy response in lung adenocarcinoma

BACKGROUND

TMPRSS2, a key molecule for SARS-CoV-2 invading human host cells, has an association with cancer. However, its association with lung cancer remains insufficiently unexplored.

METHODS

In five bulk transcriptomics datasets, one single-cell RNA sequencing (scRNA-seq) dataset and one proteomics dataset for lung adenocarcinoma (LUAD), we explored associations between TMPRSS2 expression and immune signatures, tumor progression phenotypes, genomic features, and clinical prognosis in LUAD by the bioinformatics approach. Furthermore, we performed experimental validation of the bioinformatics findings.

RESULTS

TMPRSS2 expression levels correlated negatively with the enrichment levels of both immune-stimulatory and immune-inhibitory signatures, while they correlated positively with the ratios of immune-stimulatory/immune-inhibitory signatures. It indicated that TMPRSS2 levels had a stronger negative correlation with immune-inhibitory than with immune-stimulatory signatures. TMPRSS2 downregulation correlated with increased proliferation, stemness, genomic instability, tumor progression, and worse survival in LUAD. We further validated that TMPRSS2 was downregulated with tumor progression in the LUAD cohort we collected from Jiangsu Cancer Hospital, China. In vitro and in vivo experiments verified the association of TMPRSS2 deficiency with increased tumor cell proliferation and invasion and antitumor immunity in LUAD. Moreover, in vivo experiments demonstrated that TMPRSS2-knockdown tumors were more sensitive to BMS-1, an inhibitor of PD-1/PD-L1.

CONCLUSIONS

TMPRSS2 is a tumor suppressor, while its downregulation is a positive biomarker of immunotherapy in LUAD. Our data provide a potential link between lung cancer and pneumonia caused by SARS-CoV-2 infection.

Strength of selection in lung tumors correlates with clinical features better than tumor mutation burden

Single nucleotide substitutions are the most common type of somatic mutations in cancer genome. The goal of this study was to use publicly available somatic mutation data to quantify negative and positive selection in individual lung tumors and test how strength of directional and absolute selection is associated with clinical features. The analysis found a significant variation in strength of selection (both negative and positive) among tumors, with median selection tending to be negative even though tumors with strong positive selection also exist. Strength of selection estimated as the density of missense mutations relative to the density of silent mutations showed only a weak correlation with tumor mutation burden. In the "all histology together" analysis we found that absolute strength of selection was strongly correlated with all clinically relevant features analyzed. In histology-stratified analysis selection was strongest in small cell lung cancer. Selection in adenocarcinoma was somewhat higher compared to squamous cell carcinoma. The study suggests that somatic mutation- based quantifying of directional and absolute selection in individual tumors can be a useful biomarker of tumor aggressiveness.

Ephs in cancer progression: complexity and context-dependent nature in signaling, angiogenesis and immunity

Eph receptors constitute the largest family of receptor tyrosine kinases, comprising 14 distinct members classified into two subgroups: EphAs and EphBs.. Despite their essential functions in normal physiological processes, accumulating evidence suggests that the involvement of the Eph family in cancer is characterized by a dual and often contradictory nature. Research indicates that Eph/ephrin bidirectional signaling influences cell-cell communication, subsequently regulating cell migration, adhesion, differentiation and proliferation. The contradictory functionalities may arise from the diversity of Eph signaling pathways and the heterogeneity of different cancer microenvironment. In this review, we aim to discuss the dual role of the Eph receptors in tumor development, attempting to elucidate the paradoxical functionality through an exploration of Eph receptor signaling pathways, angiogenesis, immune responses, and more. Our objective is to provide a comprehensive understanding of the molecular mechanisms underlying tumor development. Additionally, we will explore the evolving landscape of utilizing Eph receptors as potential targets for tumor therapy and diagnostic tools.

Evaluation of KRAS inhibitor-directed therapies for pancreatic cancer treatment

Despite significant advancements in the treatment of other cancers, pancreatic ductal adenocarcinoma (PDAC) remains one of the world's deadliest cancers. More than 90% of PDAC patients harbor a Kirsten rat sarcoma (KRAS) gene mutation. Although the clinical potential of anti-KRAS therapies has long been realized, all initial efforts to target KRAS were unsuccessful. However, with the recent development of a new generation of KRAS-targeting drugs, multiple KRAS-targeted treatment options for patients with PDAC have entered clinical trials. In this review, we provide an overview of current standard of care treatment, describe RAS signaling and the relevance of KRAS mutations, and discuss RAS isoform- and mutation-specific differences. We also evaluate the clinical efficacy and safety of mutation-selective and multi-selective inhibitors, in the context of PDAC. We then provide a comparison of clinically relevant KRAS inhibitors to second-line PDAC treatment options. Finally, we discuss putative resistance mechanisms that may limit the clinical effectiveness of KRAS-targeted therapies and provide a brief overview of promising therapeutic approaches in development that are focused on mitigating these resistance mechanisms.

Which is a real valuable screening tool for lung cancer and measure thoracic diseases, chest radiography or low-dose computed tomography?: A review on the current status of Japan and other countries

Chest radiography (CR) has been used as a screening tool for lung cancer and the use of low-dose computed tomography (LDCT) is not recommended in Japan. We need to reconsider whether CR really contributes to the early detection of lung cancer. In addition, we have not well discussed about other major thoracic disease detection by CR and LDCT compared with lung cancer despite of its high frequency. We review the usefulness of CR and LDCT as veridical screening tools for lung cancer and other thoracic diseases. In the case of lung cancer, many studies showed that LDCT has capability of early detection and improving outcomes compared with CR. Recent large randomized trial also supports former results. In the case of chronic obstructive pulmonary disease (COPD), LDCT contributes to early detection and leads to the implementation of smoking cessation treatments. In the case of pulmonary infections, LDCT can reveal tiny inflammatory changes that are not observed on CR, though many of these cases improve spontaneously. Therefore, LDCT screening for pulmonary infections may be less useful. CR screening is more suitable for the detection of pulmonary infections. In the case of cardiovascular disease (CVD), CR may be a better screening tool for detecting cardiomegaly, whereas LDCT may be a more useful tool for detecting vascular changes. Therefore, the current status of thoracic disease screening is that LDCT may be a better screening tool for detecting lung cancer, COPD, and vascular changes. CR may be a suitable screening tool for pulmonary infections and cardiomegaly.

Discovery of a Meisoindigo-Derived PROTAC as the ATM Degrader: Revolutionizing Colorectal Cancer Therapy via Synthetic Lethality with ATR Inhibitors

Meisoindigo (Mei) has long been recognized in chronic myeloid leukemia (CML) treatment. To elucidate its molecular target and mechanisms, we embarked on designing and synthesizing a series of Mei-derived PROTACs. Through this endeavor, VHL-type PROTAC 9b was identified to be highly cytotoxic against SW620, SW480, and K562 cells. Employing DiaPASEF-based quantitative proteomic analysis, in combination with extensive validation assays, we unveiled that 9b potently and selectively degraded ATM across SW620 and SW480 cells in a ubiquitin-proteasome-dependent manner. 9b-induced selective ATM degradation prompted DNA damage response cascades, thereby leading to the cell cycle arrest and cell apoptosis. This pioneering discovery renders the advent of ATM degradation for anti-cancer therapy. Notably, 9b-induced ATM degradation synergistically enhanced the efficacy of ATR inhibitor AZD6738 both in vitro and in vivo. This work establishes the synthetic lethality-inducing properties of ATR inhibitors in the ATM-deficient context, thereby providing new avenues to innovative therapies for colorectal cancer.

Musashi-2 (MSI2) regulation of DNA damage response in lung cancer

Lung cancer is one of the most common types of cancer worldwide. Non-small cell lung cancer (NSCLC), typically caused by KRAS and TP53 driver mutations, represents the majority of all new lung cancer diagnoses. Overexpression of the RNA-binding protein (RBP) Musashi-2 (MSI2) has been associated with NSCLC progression. To investigate the role of MSI2 in NSCLC development, we compared the tumorigenesis in mice with lung-specific Kras-activating mutation and Trp53 deletion, with and without Msi2 deletion (KPM2 versus KP mice). KPM2 mice showed decreased lung tumorigenesis in comparison with KP mice. In addition, KPM2 lung tumors showed evidence of decreased proliferation, but increased DNA damage, marked by increased levels of phH2AX (S139) and phCHK1 (S345), but decreased total and activated ATM. Using cell lines from KP and KPM2 tumors, and human NSCLC cell lines, we found that MSI2 directly binds ATM mRNA and regulates its translation. MSI2 depletion impaired DNA damage response (DDR) signaling and sensitized human and murine NSCLC cells to treatment with PARP inhibitors in vitro and in vivo. Taken together, we conclude that MSI2 supports NSCLC tumorigenesis, in part, by supporting repair of DNA damage by controlling expression of DDR proteins. These results suggest that targeting MSI2 may be a promising strategy for lung cancers treated with DNA-damaging agents.

Alk-rearranged lung adenocarcinoma: From molecular genetics to therapeutic targeting

Anaplastic Lymphoma Kinase (ALK) is a potent oncogenic driver of lung adenocarcinoma (LUAD). ALK is constitutively activated by gene fusion events between the ALK and other gene fusion partners in about 2-3% of LUADs, characterized by few other gene alterations. ALK-fusions are a druggable target through potent pharmacological inhibitors of tyrosine kinase activity. Thus, several ALK-TKIs (Tyrosine Kinase Inhibitors) of first-, second- and third-generation have been developed that improved the outcomes of ALK-rearranged LUADs when used as first- or second-line agents. However, resistance mechanisms greatly limit the durability of the therapeutic effects elicited by these TKIs. The molecular mechanisms responsible for these resistance mechanisms have been in part elucidated, but overcoming acquired resistance to ALK-derived therapy remains a great challenge. Some new therapeutic strategies under investigation aim to induce long-term remission in ALK-fusion positive LUADs.

Impact of KRASG12D subtype and concurrent pathogenic mutations on advanced non-small cell lung cancer outcomes

PURPOSE

Mutations in the Kirsten rat sarcoma viral (KRAS) oncogene constitute a significant driver of lung adenocarcinoma, present in 10-40% of patients, which exhibit heterogeneous clinical outcomes, mainly driven by concurrent genetic alterations. However, characterization of KRAS mutational subtypes and their impact on clinical outcomes in Latin America is limited.

METHODS

A cohort study was conducted at the National Cancer Institute (INCan) of Mexico. Individuals with advance-staged of adenocarcinoma and KRAS mutations, detected by next-generation sequencing, having undergone at least one line of therapy were included for analysis. Clinical and pathological characteristics were retrieved from institutional database from June 2014 to March 2023.

RESULTS

KRAS was identified in fifty-four (15.6%) of 346 patients, among which 50 cases were included for analysis. KRASG12D (n = 16, 32%) and KRASG12C (n = 16, 32%) represented the most prevalent subtypes. KRASG12D mutations were associated with female (p = 0.018), never smokers (p = 0.108), and concurrences with EGFR (25.0% vs. 17.6%, p = 0.124) and CDKN2A (18.8% vs. 14.7%, p = 0.157). KRASG12D patients showed a better ORR (66.6% vs. 30.0%; OR 4.66, 95% CI 1.23-17.60, p = 0.023) and on multivariate analysis was significantly associated with better PFS (HR 0.36, 95% CI 0.16-0.80; p = 0.012) and OS (HR 0.24, 95% CI 0.08-0.70; p = 0.009).

CONCLUSIONS

To our knowledge, this study represents the first effort to comprehensively characterize the molecular heterogeneity of KRAS-mutant NSCLC in Latin American patients. Our data reinforce the current view that KRAS-mutated NSCLC is not a single oncogene-driven disease and emphasizes the prognostic impact of diverse molecular profiles in this genomically defined subset of NSCLC. Further validation is warranted in larger multicenter Latin American cohorts to confirm our findings.

Links between melanoma germline risk loci, driver genes and comorbidities: insight from a tissue-specific multi-omic analysis

Genome-wide association studies (GWAS) have associated 76 loci with the risk of developing melanoma. However, understanding the molecular basis of such associations has remained a challenge because most of these loci are in non-coding regions of the genome. Here, we integrated data on epigenomic markers, three-dimensional (3D) genome organization, and expression quantitative trait loci (eQTL) from melanoma-relevant tissues and cell types to gain novel insights into the mechanisms underlying melanoma risk. This integrative approach revealed a total of 151 target genes, both near and far away from the risk loci in linear sequence, with known and novel roles in the etiology of melanoma. Using protein-protein interaction networks, we identified proteins that interact-directly or indirectly-with the products of the target genes. The interacting proteins were enriched for known melanoma driver genes. Further integration of these target genes into tissue-specific gene regulatory networks revealed patterns of gene regulation that connect melanoma to its comorbidities. Our study provides novel insights into the biological implications of genetic variants associated with melanoma risk.

Molecular mechanisms underlying the regulation of tumour suppressor genes in lung cancer

Tumour suppressor genes play a cardinal role in the development of a large array of human cancers, including lung cancer, which is one of the most frequently diagnosed cancers worldwide. Therefore, extensive studies have been committed to deciphering the underlying mechanisms of alterations of tumour suppressor genes in governing tumourigenesis, as well as resistance to cancer therapies. In spite of the encouraging clinical outcomes demonstrated by lung cancer patients on initial treatment, the subsequent unresponsiveness to first-line treatments manifested by virtually all the patients is inherently a contentious issue. In light of the aforementioned concerns, this review compiles the current knowledge on the molecular mechanisms of some of the tumour suppressor genes implicated in lung cancer that are either frequently mutated and/or are located on the chromosomal arms having high LOH rates (1p, 3p, 9p, 10q, 13q, and 17p). Our study identifies specific genomic loci prone to LOH, revealing a recurrent pattern in lung cancer cases. These loci, including 3p14.2 (FHIT), 9p21.3 (p16INK4a), 10q23 (PTEN), 17p13 (TP53), exhibit a higher susceptibility to LOH due to environmental factors such as exposure to DNA-damaging agents (carcinogens in cigarette smoke) and genetic factors such as chromosomal instability, genetic mutations, DNA replication errors, and genetic predisposition. Furthermore, this review summarizes the current treatment landscape and advancements for lung cancers, including the challenges and endeavours to overcome it. This review envisages inspired researchers to embark on a journey of discovery to add to the list of what was known in hopes of prompting the development of effective therapeutic strategies for lung cancer.

Personalized Driver Gene Prediction Using Graph Convolutional Networks with Conditional Random Fields

Cancer is a complex and evolutionary disease mainly driven by the accumulation of genetic variations in genes. Identifying cancer driver genes is important. However, most related studies have focused on the population level. Cancer is a disease with high heterogeneity. Thus, the discovery of driver genes at the individual level is becoming more valuable but is a great challenge. Although there have been some computational methods proposed to tackle this challenge, few can cover all patient samples well, and there is still room for performance improvement. In this study, to identify individual-level driver genes more efficiently, we propose the PDGCN method. PDGCN integrates multiple types of data features, including mutation, expression, methylation, copy number data, and system-level gene features, along with network structural features extracted using Node2vec in order to construct a sample-gene interaction network. Prediction is performed using a graphical convolutional neural network model with a conditional random field layer, which is able to better combine the network structural features with biological attribute features. Experiments on the ACC (Adrenocortical Cancer) and KICH (Kidney Chromophobe) datasets from TCGA (The Cancer Genome Atlas) demonstrated that the method performs better compared to other similar methods. It can identify not only frequently mutated driver genes, but also rare candidate driver genes and novel biomarker genes. The results of the survival and enrichment analyses of these detected genes demonstrate that the method can identify important driver genes at the individual level.

Prognostic and predictive biomarkers in non-small cell lung carcinoma

Lung cancer is the most common cause of cancer-related deaths globally, with the highest mortality rates among both men and women. Most lung cancers are diagnosed at late stages, necessitating systemic therapy. Modern clinical management of lung cancer relies heavily upon application of biomarkers, which guide the selection of systemic treatment. Here, we provide an overview of currently approved and emerging biomarkers of non-small cell lung cancer (NSCLC), including EGFR, ALK, ROS1, RET, NTRK1-3, KRAS, BRAF, MET, ERBB2/HER2, NRG1, PD-L1, TROP2, and CEACAM5. For practical purposes, we divide these biomarkers into genomic and protein markers, based on the tested substrate. We review the biology and epidemiology of the genomic and proteomic biomarkers, discuss optimal diagnostic assays for their detection, and highlight their contribution to the contemporary clinical management of NSCLC.

Patient-derived tumor organoids with p53 mutations, and not wild-type p53, are sensitive to synergistic combination PARP inhibitor treatment

Poly (ADP-ribose) polymerase inhibitors (PARPi) are used for patients with BRCA1/2 mutations, but patients with other mutations may benefit from PARPi treatment. Another mutation that is present in more cancers than BRCA1/2 is mutation to the TP53 gene. In 2D breast cancer cell lines, mutant p53 (mtp53) proteins tightly associate with replicating DNA and Poly (ADP-ribose) polymerase (PARP) protein. Combination drug treatment with the alkylating agent temozolomide and the PARPi talazoparib kills mtp53 expressing 2D grown breast cancer cell lines. We evaluated the sensitivity to the combination of temozolomide plus PARPi talazoparib treatment to breast and lung cancer patient-derived tumor organoids (PDTOs). The combination of the two drugs was synergistic for a cytotoxic response in PDTOs with mtp53 but not for PDTOs with wtp53. The combination of talazoparib and temozolomide induced more DNA double-strand breaks in mtp53 expressing organoids than in wild-type p53 expressing organoids as shown by increased γ-H2AX protein expression. Moreover, breast cancer tissue microarrays (TMAs) showed a positive correlation between stable p53 and high PARP1 expression in sub-groups of breast cancers, which may indicate sub-classes of breast cancers sensitive to PARPi therapy. These results suggest that mtp53 could be a biomarker to predict response to the combination of PARPi talazoparib-temozolomide treatment.

Profiling of ERBB receptors and downstream pathways reveals selectivity and hidden properties of ERBB4 antagonists

ERBB receptor tyrosine kinases are involved in development and diseases like cancer, cardiovascular, neurodevelopmental, and mental disorders. Although existing drugs target ERBB receptors, the next generation of drugs requires enhanced selectivity and understanding of physiological pathway responses to improve efficiency and reduce side effects. To address this, we developed a multilevel barcoded reporter profiling assay, termed 'ERBBprofiler', in living cells to monitor the activity of all ERBB targets and key physiological pathways simultaneously. This assay helps differentiate on-target therapeutic effects from off-target and off-pathway side effects of ERBB antagonists. To challenge the assay, eight established ERBB antagonists were profiled. Known effects were confirmed, and previously uncharacterized properties were discovered, such as pyrotinib's preference for ERBB4 over EGFR. Additionally, two lead compounds selectively targeting ERBB4 were profiled, showing promise for clinical trials. Taken together, this multiparametric profiling approach can guide early-stage drug development and lead to improved future therapeutic interventions.

Identification of tumor heterogeneity associated with KRAS/TP53 co-mutation status in lung adenocarcinoma based on single-cell RNA sequencing

Lung cancer stands as the predominant cause of cancer-related mortality globally. Lung adenocarcinoma (LUAD), being the most prevalent subtype, garners extensive attention due to its notable heterogeneity, which significantly influences tumor development and treatment approaches. This research leverages single-cell RNA sequencing (scRNA-seq) datasets to delve into the impact of KRAS/TP53 co-mutation status on LUAD. Moreover, utilizing the TCGA-LUAD dataset, we formulated a novel predictive risk model, comprising seven prognostic genes, through LASSO regression, and subjected it to both internal and external validation sets. The study underscores the profound impact of KRAS/TP53 co-mutational status on the tumor microenvironment (TME) of LUAD. Crucially, KRAS/TP53 co-mutation markedly influences the extent of B cell infiltration and various immune-related pathways within the TME. The newly developed predictive risk model exhibited robust performance across both internal and external validation sets, establishing itself as a viable independent prognostic factor. Additionally, in vitro experiments indicate that MELTF and PLEK2 can modulate the invasion and proliferation of human non-small cell lung cancer cells. In conclusion, we elucidated that KRAS/TP53 co-mutations may modulate TME and patient prognosis by orchestrating B cells and affiliated pathways. Furthermore, we spotlight that MELTF and PLEK2 not only function as prognostic indicators for LUAD, but also lay the foundation for the exploration of innovative therapeutic approaches.

Oncogenic alterations in advanced NSCLC: a molecular super-highway

Lung cancer ranks among the most common cancers world-wide and is the first cancer-related cause of death. The classification of lung cancer has evolved tremendously over the past two decades. Today, non-small cell lung cancer (NSCLC), particularly lung adenocarcinoma, comprises a multitude of molecular oncogenic subsets that change both the prognosis and management of disease.Since the first targeted oncogenic alteration identified in 2004, with the epidermal growth factor receptor (EGFR), there has been unprecedented progress in identifying and targeting new molecular alterations. Almost two decades of experience have allowed scientists to elucidate the biological function of oncogenic drivers and understand and often overcome the molecular basis of acquired resistance mechanisms. Today, targetable molecular alterations are identified in approximately 60% of lung adenocarcinoma patients in Western populations and 80% among Asian populations. Oncogenic drivers are largely enriched among non-smokers, east Asians, and younger patients, though each alteration has its own patient phenotype.The current landscape of druggable molecular targets includes EGFR, anaplastic lymphoma kinase (ALK), v-raf murine sarcoma viral oncogene homolog B (BRAF), ROS proto-oncogene 1 (ROS1), Kirstin rat sarcoma virus (KRAS), human epidermal receptor 2 (HER2), c-MET proto-oncogene (MET), neurotrophic receptor tyrosine kinase (NTRK), rearranged during transfection (RET), neuregulin 1 (NRG1). In addition to these known targets, others including Phosphoinositide 3-kinases (PI3K) and fibroblast growth factor receptor (FGFR) have garnered significant attention and are the subject of numerous ongoing trials.In this era of personalized, precision medicine, it is of paramount importance to identify known or potential oncogenic drivers in each patient. The development of targeted therapy is mirrored by diagnostic progress. Next generation sequencing offers high-throughput, speed and breadth to identify molecular alterations in entire genomes or targeted regions of DNA or RNA. It is the basis for the identification of the majority of current druggable alterations and offers a unique window into novel alterations, and de novo and acquired resistance mechanisms.In this review, we discuss the diagnostic approach in advanced NSCLC, focusing on current oncogenic driver alterations, through their pathophysiology, management, and future perspectives. We also explore the shortcomings and hurdles encountered in this rapidly evolving field.

NSCLC: from tumorigenesis, immune checkpoint misuse to current and future targeted therapy

Non-small cell lung cancer (NSCLC) is largely promoted by a multistep tumorigenesis process involving various genetic and epigenetic alterations, which essentially contribute to the high incidence of mortality among patients with NSCLC. Clinical observations revealed that NSCLC also co-opts a multifaceted immune checkpoint dysregulation as an important driving factor in NSCLC progression and development. For example, a deregulated PI3K/AKT/mTOR pathway has been noticed in 50-70% of NSCLC cases, primarily modulated by mutations in key oncogenes such as ALK, EGFR, KRAS, and others. Additionally, genetic association studies containing patient-specific factors and local reimbursement criteria expose/reveal mutations in EGFR/ALK/ROS/BRAF/KRAS/PD-L1 proteins to determine the suitability of available immunotherapy or tyrosine kinase inhibitor therapy. Thus, the expression of such checkpoints on tumors and immune cells is pivotal in understanding the therapeutic efficacy and has been extensively studied for NSCLC treatments. Therefore, this review summarizes current knowledge in NSCLC tumorigenesis, focusing on its genetic and epigenetic intricacies, immune checkpoint dysregulation, and the evolving landscape of targeted therapies. In the context of current and future therapies, we emphasize the significance of antibodies targeting PD-1/PD-L1 and CTLA-4 interactions as the primary therapeutic strategy for immune system reactivation in NSCLC. Other approaches involving the promising potential of nanobodies, probodies, affibodies, and DARPINs targeting immune checkpoints are also described; these are under active research or clinical trials to mediate immune regulation and reduce cancer progression. This comprehensive review underscores the multifaceted nature, current state and future directions of NSCLC research and treatment.

Baseline circulating tumour DNA and interim PET predict response in relapsed/refractory classical Hodgkin lymphoma

Reliable biomarkers for early identification of treatment failure in relapsed/refractory (r/r) classical Hodgkin lymphoma (cHL) are lacking. Circulating tumour DNA (ctDNA) profiling has emerged as a powerful predictive and prognostic tool in several haemopoietic and non-haemopoietic malignancies and may guide rational treatment choices in r/r cHL. To assess the predictive and prognostic value of ctDNA, we performed a retrospective analysis on 55 r/r cHL patients treated with the bendamustine, gemcitabine and vinorelbine (BEGEV) regimen and additionally evaluated the potential utility of integrating ctDNA with interim [18 F]-FDG positron emission tomography (iPET). Baseline ctDNA genotyping in r/r cHL mirrored gene mutations and pathways involved in newly diagnosed cHL. We found that baseline ctDNA quantification and serial ctDNA monitoring have prognostic value in r/r cHL receiving salvage chemotherapy. Lastly, integrating ctDNA quantification with iPET evaluation may improve the early identification of patients at high risk of failing standard salvage therapy, who may benefit from an early switch to immunotherapeutic agents. Collectively, our results support the implementation of non-invasive methods to detect minimal residual disease in recurrent cHL and justify its prospective evaluation in appropriately designed clinical trials.

Adaptation of a mutual exclusivity framework to identify driver mutations within oncogenic pathways

Distinguishing genomic alterations in cancer-associated genes that have functional impact on tumor growth and disease progression from the ones that are passengers and confer no fitness advantage have important clinical implications. Evidence-based methods for nominating drivers are limited by existing knowledge on the oncogenic effects and therapeutic benefits of specific variants from clinical trials or experimental settings. As clinical sequencing becomes a mainstay of patient care, applying computational methods to mine the rapidly growing clinical genomic data holds promise in uncovering functional candidates beyond the existing knowledge base and expanding the patient population that could potentially benefit from genetically targeted therapies. We propose a statistical and computational method (MAGPIE) that builds on a likelihood approach leveraging the mutual exclusivity pattern within an oncogenic pathway for identifying probabilistically both the specific genes within a pathway and the individual mutations within such genes that are truly the drivers. Alterations in a cancer-associated gene are assumed to be a mixture of driver and passenger mutations with the passenger rates modeled in relationship to tumor mutational burden. We use simulations to study the operating characteristics of the method and assess false-positive and false-negative rates in driver nomination. When applied to a large study of primary melanomas, the method accurately identifies the known driver genes within the RTK-RAS pathway and nominates several rare variants as prime candidates for functional validation. A comprehensive evaluation of MAGPIE against existing tools has also been conducted leveraging the Cancer Genome Atlas data.

Antitumor efficacy of synthesized Ag-Au nanocomposite loaded with PEG and ascorbic acid in human lung cancer stem cells

Lung cancer is the leading cause of mortality worldwide of which non-small cell lung carcinoma constitutes majority of the cases. High mortality is attributed to early metastasis, late diagnosis, ineffective treatment and tumor relapse. Chemotherapy and radiotherapy form the mainstay of its treatment. However, their associated side effects involving kidneys, nervous system, gastrointestinal tract, and liver further adds to dismal outcome. These disadvantages of conventional treatment can be circumvented by use of engineered nanoparticles for improved effectiveness with minimal side effects. In this study we have synthesized silver gold nanocomposite (Ag-Au NC) using polyethylene glycol and l-ascorbic acid as surfactant and reducing agent respectively. Synthesized nanocomposite was characterized by ultraviolet-visible absorption, dynamic light scattering, scanning and transmission electron microscopy. Compositional analysis was carried out by energy dispersive X-ray analysis and average pore diameter was estimated using Barrett-Joyner-Halenda method. In-silico molecular docking analysis of the synthesized NC against active regions of epidermal growth factor receptor revealed good binding energy. Subsequently, we investigated the effect of NC on growth and stem cell attributes of A549 lung cancer cells. Results showed that NC was effective in inhibiting A549 cell proliferation, induced DNA damage, G2/M phase arrest and apoptosis. Further, tumor cell migration and spheroid formation were also negatively affected. NC also enhanced reactive oxygen species generation and mitochondrial depolarization. In addition, the effect of NC on putative cancer stem cells in A549 cells was evaluated. We found that Ag-Au NC at IC50 targeted CD44, CD24, CD166, CD133 and CD326 positive cancer stem cells and induced apoptosis. CD166 positive cells were relatively resistance to apoptosis. Together our results demonstrate the anticancer efficacy of Ag-Au NC mediated by a mechanism involving cell cycle arrest and mitochondrial derangement.

Contrasting Effects of Cancer-Associated Mutations in EphA3 and EphB2 Kinases

Erythropoietin-producing hepatoma (Eph) receptors are a family of tyrosine kinases that can act as tumor promoters or tumor suppressors, depending on the receptor and cancer cell type. Cancer-associated somatic mutations have been identified in all Eph receptors, but in most cases, the functional effects of the mutations are unknown. In this study, we expressed and purified the kinase domains of wild-type (WT) EphA3 and EphB2 along with 16 cancer-associated mutants. We identified mutations that decrease EphA3 activity and both activating and inhibitory mutations in EphB2. To shed light on the mechanisms by which the mutations altered kinase activity, we measured the thermal stabilities of the enzymes and performed steady-state kinetic experiments. We also expressed the full-length receptors in HEK293T cells to determine the cellular effects. WT EphB2 promoted downstream ERK signaling, while a kinase-inactive mutant (S706F) was similar to the control cells. In contrast, WT EphA3 (but not loss-of-function mutants) inhibited ERK signaling. The reciprocal effects of EphB2 and EphA3 on ERK phosphorylation in HEK293T cells were also evident in Ras-GTP loading. Thus, consistent with the dual roles of Eph receptors as tumor promoters and tumor suppressors, somatic mutations have the potential to increase or decrease Eph function, resulting in changes in the downstream signaling transduction.

CellCharter reveals spatial cell niches associated with tissue remodeling and cell plasticity

Tissues are organized in cellular niches, the composition and interactions of which can be investigated using spatial omics technologies. However, systematic analyses of tissue composition are challenged by the scale and diversity of the data. Here we present CellCharter, an algorithmic framework to identify, characterize, and compare cellular niches in spatially resolved datasets. CellCharter outperformed existing approaches and effectively identified cellular niches across datasets generated using different technologies, and comprising hundreds of samples and millions of cells. In multiple human lung cancer cohorts, CellCharter uncovered a cellular niche composed of tumor-associated neutrophil and cancer cells expressing markers of hypoxia and cell migration. This cancer cell state was spatially segregated from more proliferative tumor cell clusters and was associated with tumor-associated neutrophil infiltration and poor prognosis in independent patient cohorts. Overall, CellCharter enables systematic analyses across data types and technologies to decode the link between spatial tissue architectures and cell plasticity.

Extensive prediction of drug response in mutation-subtype-specific LUAD with machine learning approach

Background

Lung cancer is the most prevalent cancer diagnosis and the leading cause of cancer death worldwide. Therapeutic failure in lung cancer (LUAD) is heavily influenced by drug resistance. This challenge stems from the diverse cell populations within the tumor, each having unique genetic, epigenetic, and phenotypic profiles. Such variations lead to varied therapeutic responses, thereby contributing to tumor relapse and disease progression.

Methods

The Genomics of Drug Sensitivity in Cancer (GDSC) database was used in this investigation to obtain the mRNA expression dataset, genomic mutation profile, and drug sensitivity information of NSCLS. Machine Learning (ML) methods, including Random Forest (RF), Artificial Neurol Network (ANN), and Support Vector Machine (SVM), were used to predict the response status of each compound based on the mRNA and mutation characteristics determined using statistical methods. The most suitable method for each drug was proposed by comparing the prediction accuracy of different ML methods, and the selected mRNA and mutation characteristics were identified as molecular features for the drug-responsive cancer subtype. Finally, the prognostic influence of molecular features on the mutational subtype of LUAD in publicly available datasets.

Results

Our analyses yielded 1,564 gene features and 45 mutational features for 46 drugs. Applying the ML approach to predict the drug response for each medication revealed an upstanding performance for SVM in predicting Afuresertib drug response (area under the curve [AUC] 0.875) using CIT, GAS2L3, STAG3L3, ATP2B4-mut, and IL15RA-mut as molecular features. Furthermore, the ANN algorithm using 9 mRNA characteristics demonstrated the highest prediction performance (AUC 0.780) in Gefitinib with CCL23-mut.

Conclusion

This work extensively investigated the mRNA and mutation signatures associated with drug response in LUAD using a machine-learning approach and proposed a priority algorithm to predict drug response for different drugs.

Whole-genome sequencing reveals the molecular implications of the stepwise progression of lung adenocarcinoma

The mechanism underlying the development of tumors, particularly at early stages, still remains mostly elusive. Here, we report whole-genome long and short read sequencing analysis of 76 lung cancers, focusing on very early-stage lung adenocarcinomas such as adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma. The obtained data is further integrated with bulk and spatial transcriptomic data and epigenomic data. These analyses reveal key events in lung carcinogenesis. Minimal somatic mutations in pivotal driver mutations and essential proliferative factors are the only detectable somatic mutations in the very early-stage of AIS. These initial events are followed by copy number changes and global DNA hypomethylation. Particularly, drastic changes are initiated at the later AIS stage, i.e., in Noguchi type B tumors, wherein cancer cells are exposed to the surrounding microenvironment. This study sheds light on the pathogenesis of lung adenocarcinoma from integrated pathological and molecular viewpoints.

Characterization of 164 patients with NRAS mutated non-small cell lung cancer (NSCLC)

BACKGROUND

NRAS mutations are observed in less than 1% of non-small cell lung cancer (NSCLC). Clinical data regarding this rare subset of lung cancer are scarce and response to systemic treatment such as chemotherapy or immune checkpoint inhibitors (ICI) has never been reported.

METHODS

All consecutive patients with an NRAS mutated NSCLC, diagnosed between August 2014 and November 2020 in 14 French centers, were included. Clinical and molecular data were collected and reviewed from medical records.

RESULTS

Out of the 164 included patients, 106 (64.6%) were men, 150 (91.5%) were current or former smokers, and 104 (63.4%) had stage IV NSCLC at diagnosis. The median age was 62 years, and the most frequent histology was adenocarcinoma (81.7%). NRAS activating mutations were mostly found in codon 61 (70%), while codon 12 and 13 alterations were observed in 16.5% and 4.9% of patients, respectively. Programmed death ligand-1 expression level <1%/1-49%/≥50% were respectively found in 30.8%/27.1%/42.1% of tumors. With a median follow-up of 12.5 months, median overall survival (OS) of stage IV patients was 15.3 months (95% CI 9.9-27.6). No significant difference in OS was found according to the type of mutation (codon 61 vs. other), HR = 1.12 (95% CI 0.65-1.95). Among stage IV patients treated with platinum-based doublet (n = 66), ICI (n = 48), or combination of both (n = 10), objective response rate, and median progression free survival were respectively 45% and 5.8 months, 35% and 6.9 months, 70% and 8.6 months.

CONCLUSION

NRAS mutated NSCLC are characterized by a high frequency of smoking history and codon 61 mutations. Further studies are needed to confirm the encouraging outcome of immunotherapy in combination with chemotherapy.

SCN4B inhibits the progression of lung adenocarcinoma and is associated with better prognosis

INTRODUCTION

Lung adenocarcinoma (LUAD) is the major type of non-small cell lung cancer with low a survival rate caused by metastasis. SCN4B encoding voltage-gated sodium channel β subunit is regarded as a metastasis-suppressor gene. We aim to explore how SCN4B influences the progression and prognosis of LUAD.

METHODS

The gene expression profiles of 585 LUAD samples in TCGA and GSE31210, GSE116959, and GSE72094 datasets from the GEO database were downloaded for analysis. Differentially expressed genes were obtained through the "limma" package. The "clusterProfiler" package was used to conduct GSEA. Survival analysis was conducted via "survival" and "survminer" packages. Transcription factors regulating SCN4B expression were screened by correlation analysis and further predicted by FIMO. Infiltration of immune cells was analyzed by CIBERSORT. ESTIMATE algorithm was used to evaluate the immune-related scores.

RESULTS

SCN4B expressed higher in normal samples than in LUAD samples and higher in female samples than male samples. One hundred and twenty-six pathways were significantly enriched between high and low SCN4B expression groups. Six transcription factors' expressions were positively related to SCN4B expression, and ChIP-seq data from "Cistrome" verified that TAL1 and ERG might bind to the upstream sequence of SCN4B. SCN4B expression was significantly correlated with activated memory CD4 T cells, resting mast cells, and monocytes. TMB status, three scores based on ESTIMATE algorithm, and expression of three immune checkpoints showed significant differences between SCN4B high- and low-expression groups. SCN4B could be considered as an independent prognostic signature of LUAD patients that higher expression represents a better prognosis.

CONCLUSION

SCN4B expresses higher in normal samples, and SCN4B is able to be an independent prognostic signature for LUAD patients. TAL1 and ERG may regulate the expression of SCN4B by binding its upstream sequences. Our research is valuable in improving the effectiveness of treatment in LUAD.

Circulating tumor DNA as liquid biopsy in lung cancer: Biological characteristics and clinical integration

Lung cancer maintains high morbidity and mortality rate globally despite significant advancements in diagnosis and treatment in the era of precision medicine. Pathological analysis of tumor tissue, the current gold standard for lung cancer diagnosis, is intrusive and intrinsically confined to evaluating the limited amount of tissues that could be physically extracted. However, tissue biopsy has several limitations, including the invasiveness of the procedure and difficulty in obtaining samples for patients at advanced stages., there Additionally,has been no major breakthrough in tumor biomarkers with high specificity and sensitivity, particularly for early-stage lung cancer. Liquid biopsy has been considered a feasible auxiliary tool for tearly dianosis, evaluating treatment responses and monitoring prognosis of lung cancer. Circulating tumor DNA (ctDNA), an ideal biomarker of liquid biopsy, has emerged as one of the most reliable tools for monitoring tumor processes at molecular levels. Herein, this review focuses on tumor heterogeneity to elucidate the superiority of liquid biopsy and retrospectively discussdeciphersolution. We systematically elaborate ctDNA biological characteristics, introduce methods for ctDNA detection, and discuss the current role of plasma ctDNA in lung cancer management. Finally, we summarize the drawbacks of ctDNA analysis and highlight its potential clinical application in lung cancer.

Activation of KrasG12D in Subset of Alveolar Type II Cells Enhances Cellular Plasticity in Lung Adenocarcinoma

We have previously identified alveolar type II cell as the cell-of-origin of KrasG12D-induced lung adenocarcinoma using cell lineage-specific inducible Cre mouse models. Using gain-of-function and loss-of-function genetic models, we discovered that active Notch signaling and low Sox2 levels dictate the ability of type II cells to proliferate and progress into lung adenocarcinoma upon KrasG12D activation. Here, we examine the phenotype of type II cells after Kras activation and find evidence for proliferation of cells that coexpress type I and type II markers. Three-dimensional organoid culture and transplantation studies determine that these dual-positive cells are highly plastic and tumor initiating in vivo. RNA sequencing analysis reveals that these dual-positive cells are enriched in Ras/MAPK, EGFR, and Notch pathways. Furthermore, the proliferation of these cells requires active Notch signaling and is inhibited by genetic/chemical Sox2 upregulation. Our findings could provide new therapeutic strategies to target KRAS-activated lung adenocarcinomas.

SIGNIFICANCE

Identification of progenitor like tumor-initiating cells in KRAS-mutant lung adenocarcinoma may allow development of novel targeted therapeutics.