Tracking the Evolution of Non-Small-Cell Lung Cancer

Circulating Tumor DNA Dynamics Reveal KRAS G12C Mutation Heterogeneity and Response to Treatment with the KRAS G12C Inhibitor Divarasib in Solid Tumors

PURPOSE

To inform prognosis, treatment response, disease biology, and KRAS G12C mutation heterogeneity, we conducted exploratory circulating tumor DNA (ctDNA) profiling on 134 patients with solid tumors harboring a KRAS G12C mutation treated with single-agent divarasib (GDC-6036) in a phase 1 study.

EXPERIMENTAL DESIGN

Plasma samples were collected for serial ctDNA profiling at baseline (cycle 1 day 1 prior to treatment) and multiple on-treatment time points (cycle 1 day 15 and cycle 3 day 1).

RESULTS

KRAS G12C ctDNA was detectable from plasma samples in 72.9% (43/59) and 92.6% (50/54) of patients with non-small cell lung cancer and colorectal cancer, respectively, the majority of whom were eligible for study participation based on a local test detecting the KRAS G12C mutation in tumor tissue. Baseline ctDNA tumor fraction was associated with tumor type, disease burden, and metastatic sites. A decline in ctDNA level was observed as early as cycle 1 day 15. Serial assessment showed a decline in ctDNA tumor fraction associated with response and progression-free survival. Except for a few cases of KRAS G12C sub-clonality, on-treatment changes in KRAS G12C variant allele frequency mirrored changes in the overall ctDNA tumor fraction.

CONCLUSIONS

Across tumor types, the KRAS G12C mutation likely represents a truncal mutation in the majority of patients. Rapid and deep decline in ctDNA tumor fraction was observed in patients responding to divarasib treatment. Early on-treatment dynamics of ctDNA were associated with patient outcomes and tumor response to divarasib treatment.

Circulating tumor cells: from new biological insights to clinical practice

The primary reason for high mortality rates among cancer patients is metastasis, where tumor cells migrate through the bloodstream from the original site to other parts of the body. Recent advancements in technology have significantly enhanced our comprehension of the mechanisms behind the bloodborne spread of circulating tumor cells (CTCs). One critical process, DNA methylation, regulates gene expression and chromosome stability, thus maintaining dynamic equilibrium in the body. Global hypomethylation and locus-specific hypermethylation are examples of changes in DNA methylation patterns that are pivotal to carcinogenesis. This comprehensive review first provides an overview of the various processes that contribute to the formation of CTCs, including epithelial-mesenchymal transition (EMT), immune surveillance, and colonization. We then conduct an in-depth analysis of how modifications in DNA methylation within CTCs impact each of these critical stages during CTC dissemination. Furthermore, we explored potential clinical implications of changes in DNA methylation in CTCs for patients with cancer. By understanding these epigenetic modifications, we can gain insights into the metastatic process and identify new biomarkers for early detection, prognosis, and targeted therapies. This review aims to bridge the gap between basic research and clinical application, highlighting the significance of DNA methylation in the context of cancer metastasis and offering new avenues for improving patient outcomes.

Exploring the clinical utility of liquid biopsy with cfDNA in cancer: A systematic review

Various tumor cells may exhibit different genetic or phenotypic characteristics. This phenomenon of cancer cells, known as Tumor Heterogeneity, is responsible for multiple cancer sites caused in a single patient through metastases. It is possible that the biopsy of the most accessible metastasis will not provide enough information to reexamine tumor features and make therapeutic recommendations. Liquid biopsy is a diagnostic technique that probes metastatic deposits from biofluids like peripheral blood for cell-free DNA (cfDNA)/circulating tumor DNA (ctDNA) from cancer patients. This analysis provides researchers and oncologists a comprehensive insight into therapeutic targets and treatment resistance-causing gene alterations. Various studies have validated that cfDNA/ctDNA may be essential in tumor analysis, constituting the need for the identification of cancer cells that may reactivate and proliferate, causing the disease to reoccur. This detection is also called Minimal Residual Disease (MRD) and shares insights on the efficiency of the treatment regimen and if the cancer cells have developed resistance to a specific treatment regimen. In this review, the significance of cfDNA/ctDNA as a possible diagnostic, prognostic, or monitoring biomarker for solid tumors has been evaluated in recent studies, and its clinical relevance in routine cancer clinics in India has been reviewed.

Multiple primary lung cancer: Updates and perspectives

Management of multiple primary lung cancer (MPLC) remains challenging, partly due to its increasing incidence, especially with the significant rise in cases of multiple lung nodules caused by low-dose computed tomography screening. Moreover, the indefinite pathogenesis, diagnostic criteria, and treatment selection add to the complexity. In recent years, there have been continuous efforts to dissect the molecular characteristics of MPLC and explore new diagnostic approaches as well as treatment modalities, which will be reviewed here, with a focus on newly emerging evidence and future perspectives, hope to provide new insights into the management of MPLC and serve as inspiration for future research related to MPLC.

Circulating tumor DNA to guide diagnosis and treatment of localized and locally advanced non-small cell lung cancer

Liquid biopsy is a minimally invasive method for biomarkers detection in body fluids, particularly in blood, which offers an elevated and growing number of clinical applications in oncology. As a result of the improvement in the techniques for DNA analysis, above all next-generation sequencing (NGS) assays, circulating tumor DNA (ctDNA) has become the most informing tumor-derived material for most types of cancer, including non-small cell lung cancer (NSCLC). Although ctDNA concentration is higher in patients with advanced tumors, it can be detected even in patients with early-stage disease. Therefore, numerous clinical applications of ctDNA in the management of early-stage lung cancer are emerging, such as lung cancer screening, the identification of minimal residual disease (MRD), and the prediction of relapse before radiologic progression. Moreover, a high number of clinical trials are ongoing to better define the impact of ctDNA evaluation in this setting. Aim of this review is to offer a comprehensive overview of the most relevant implementations in using ctDNA for the management of early-stage lung cancer, addressing available data, technical aspects, limitations, and future perspectives.

Premalignant Progression in the Lung: Knowledge Gaps and Novel Opportunities for Interception of Non-Small Cell Lung Cancer. An Official American Thoracic Society Research Statement

Rationale: Despite significant advances in precision treatments and immunotherapy, lung cancer is the most common cause of cancer death worldwide. To reduce incidence and improve survival rates, a deeper understanding of lung premalignancy and the multistep process of tumorigenesis is essential, allowing timely and effective intervention before cancer development. Objectives: To summarize existing information, identify knowledge gaps, formulate research questions, prioritize potential research topics, and propose strategies for future investigations into the premalignant progression in the lung. Methods: An international multidisciplinary team of basic, translational, and clinical scientists reviewed available data to develop and refine research questions pertaining to the transformation of premalignant lung lesions to advanced lung cancer. Results: This research statement identifies significant gaps in knowledge and proposes potential research questions aimed at expanding our understanding of the mechanisms underlying the progression of premalignant lung lesions to lung cancer in an effort to explore potential innovative modalities to intercept lung cancer at its nascent stages. Conclusions: The identified gaps in knowledge about the biological mechanisms of premalignant progression in the lung, together with ongoing challenges in screening, detection, and early intervention, highlight the critical need to prioritize research in this domain. Such focused investigations are essential to devise effective preventive strategies that may ultimately decrease lung cancer incidence and improve patient outcomes.

Tumor evolution metrics predict recurrence beyond 10 years in locally advanced prostate cancer

Cancer evolution lays the groundwork for predictive oncology. Testing evolutionary metrics requires quantitative measurements in controlled clinical trials. We mapped genomic intratumor heterogeneity in locally advanced prostate cancer using 642 samples from 114 individuals enrolled in clinical trials with a 12-year median follow-up. We concomitantly assessed morphological heterogeneity using deep learning in 1,923 histological sections from 250 individuals. Genetic and morphological (Gleason) diversity were independent predictors of recurrence (hazard ratio (HR) = 3.12 and 95% confidence interval (95% CI) = 1.34-7.3; HR = 2.24 and 95% CI = 1.28-3.92). Combined, they identified a group with half the median time to recurrence. Spatial segregation of clones was also an independent marker of recurrence (HR = 2.3 and 95% CI = 1.11-4.8). We identified copy number changes associated with Gleason grade and found that chromosome 6p loss correlated with reduced immune infiltration. Matched profiling of relapse, decades after diagnosis, confirmed that genomic instability is a driving force in prostate cancer progression. This study shows that combining genomics with artificial intelligence-aided histopathology leads to the identification of clinical biomarkers of evolution.

Spatial multi-omics: deciphering technological landscape of integration of multi-omics and its applications

The emergence of spatial multi-omics has helped address the limitations of single-cell sequencing, which often leads to the loss of spatial context among cell populations. Integrated analysis of the genome, transcriptome, proteome, metabolome, and epigenome has enhanced our understanding of cell biology and the molecular basis of human diseases. Moreover, this approach offers profound insights into the interactions between intracellular and intercellular molecular mechanisms involved in the development, physiology, and pathogenesis of human diseases. In this comprehensive review, we examine current advancements in multi-omics technologies, focusing on their evolution and refinement over the past decade, including improvements in throughput and resolution, modality integration, and accuracy. We also discuss the pivotal contributions of spatial multi-omics in revealing spatial heterogeneity, constructing detailed spatial atlases, deciphering spatial crosstalk in tumor immunology, and advancing translational research and cancer therapy through precise spatial mapping.

The Spiral Model of Evolution: Stable Life Forms of Organisms and Unstable Life Forms of Cancers

If one must prioritize among the vast array of contributing factors to cancer evolution, environmental-stress-mediated chromosome instability (CIN) should easily surpass individual gene mutations. CIN leads to the emergence of genomically unstable life forms, enabling them to grow dominantly within the stable life form of the host. In contrast, stochastic gene mutations play a role in aiding the growth of the cancer population, with their importance depending on the initial emergence of the new system. Furthermore, many specific gene mutations among the many available can perform this function, decreasing the clinical value of any specific gene mutation. Since these unstable life forms can respond to treatment differently than stable ones, cancer often escapes from drug treatment by forming new systems, which leads to problems during the treatment for patients. To understand how diverse factors impact CIN-mediated macroevolution and genome integrity-ensured microevolution, the concept of two-phased cancer evolution is used to reconcile some major characteristics of cancer, such as bioenergetic, unicellular, and multicellular evolution. Specifically, the spiral of life function model is proposed, which integrates major historical evolutionary innovations and conservation with information management. Unlike normal organismal evolution in the microevolutionary phase, where a given species occupies a specific location within the spiral, cancer populations are highly heterogenous at multiple levels, including epigenetic levels. Individual cells occupy different levels and positions within the spiral, leading to supersystems of mixed cellular populations that exhibit both macro and microevolution. This analysis, utilizing karyotype to define the genetic networks of the cellular system and CIN to determine the instability of the system, as well as considering gene mutation and epigenetics as modifiers of the system for information amplification and usage, explores the high evolutionary potential of cancer. It provides a new, unified understanding of cancer as a supersystem, encouraging efforts to leverage the dynamics of CIN to develop improved treatment options. Moreover, it offers a historically contingent model for organismal evolution that reconciles the roles of both evolutionary innovation and conservation through macroevolution and microevolution, respectively.

Exploring the biology of ctDNA release in colorectal cancer

BACKGROUND

Circulating tumor DNA (ctDNA) has emerged as a promising tool for early cancer detection and minimal residual disease monitoring. However, the biology underlying ctDNA release and its variation across cancer types and histologies remains poorly understood. This study investigated the biology behind ctDNA shedding in colorectal cancer.

METHODS

The study included a local cohort of 747 stage I-III colorectal cancer patients. All patients had ctDNA measurement prior to treatment and extensive clinical data. Primary tumor RNA sequencing and whole exome sequencing was performed in 95 and 652 patients respectively. Additionally, the study evaluated 89 non-small cell lung cancer patients from the TRACERx cohort, comprising primary tumor RNA sequencing and ctDNA measurement.

RESULTS

We found tumor size and proliferative capacity to be key factors associated with ctDNA shedding in colorectal cancer. Furthermore, we found that the secretory and CMS3 colorectal cancer subtypes exhibited lower ctDNA shedding, while microsatellite instability (MSI) tumors had higher levels of ctDNA. Mutational analysis did not reveal any genes or pathways associated with ctDNA shedding in colorectal cancer. A comparison of transcriptomic profiles across multiple cancer types demonstrated that colorectal cancer and lung squamous cell carcinoma tumors shared a high-proliferative ctDNA shedding phenotype, while lung adenocarcinoma tumors displayed a distinct low-proliferative subgroup. Additionally, proliferation levels correlated with ctDNA detection sensitivity across multiple cancer types.

CONCLUSION

These findings suggest that tumor size and proliferative capacity are drivers of ctDNA release in colorectal cancer and provide insights into the biology of ctDNA shedding on a pan-cancer level.

Radiomics in esophagogastric junction cancer: A scoping review of current status and advances

PURPOSE

This scoping review aimed to understand the advances in radiomics in esophagogastric junction (EGJ) cancer and assess the current status of radiomics in EGJ cancer.

METHODS

We conducted systematic searches of PubMed, Embase, and Web of Science databases from January 18, 2012, to January 15, 2023, to identify radiomics articles related to EGJ cancer. Two researchers independently screened the literature, extracted data, and assessed the quality of the studies using the Radiomics Quality Score (RQS) and the METhodological RadiomICs Score (METRICS) tool, respectively.

RESULTS

A total of 120 articles were retrieved from the three databases, and after screening, only six papers met the inclusion criteria. These studies investigated the role of radiomics in differentiating adenocarcinoma from squamous carcinoma, diagnosing T-stage, evaluating HER2 overexpression, predicting response to neoadjuvant therapy, and prognosis in EGJ cancer. The median score percentage of RQS was 34.7% (range from 22.2% to 38.9%). The median score percentage of METRICS was 71.2% (range from 58.2% to 84.9%).

CONCLUSION

Although there is a considerable difference between the RQS and METRICS scores of the included literature, we believe that the research value of radiomics in EGJ cancer has been revealed. In the future, while actively exploring more diagnostic, prognostic, and biological correlation studies in EGJ cancer, greater emphasis should be placed on the standardization and clinical application of radiomics.

A label-free colorimetric biosensor utilizing natural material for highly sensitive exosome detection

Exosomes, extracellular vesicles secreted by cells, play a crucial role in intercellular communication by transferring information from source cells to recipient cells. These vesicles carry important biomarkers, including nucleic acids and proteins, which provide valuable insights into the parent cells' status. As a result, exosomes have emerged as noninvasive indicators for the early diagnosis of cancer. Colorimetric biosensors have garnered significant attention due to their cost-effectiveness, simplicity, rapid response, and reproducibility. In this study, we employ sporopollenin microcapsules (SP), a natural biopolymer material derived from pollen, as a substrate for gold nanoparticles (AuNPs). By modifying the SP-Au complex with CD63 aptamers, we develop a label-free colorimetric biosensor for exosome detection. In the absence of exosomes, the SP-Au complex catalyzes the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB), resulting in a color change from colorless to blue. However, the addition of exosomes inhibits the catalytic activity of the SP-Au complex due to coverage of exosomes on AuNPs. This colorimetric biosensor exhibits high sensitivity and selectivity for exosome detection, with a detection limit of 10 particles/μL and a wide linear range of 10 - 108 particles/μL. Additionally, the SP-Au biosensor demonstrates remarkable resistance to serum protein adsorption and excellent catalytic stability even in harsh environments, making it highly suitable for clinical diagnostics.

Immunohistochemistry of p53 surrogates TP53 mutation as an accurate predictor for early-relapse of surgically resected stage I-III lung adenocarcinoma

Introduction

TP53 is a strong tumor suppressor gene; its deactivation contributes to carcinogenesis and influences clinical outcomes. However, the prognostic influence of p53 deactivation on early relapse in patients with surgically resected non-small cell lung cancer remains unclear.

Materials and methods

A cohort of 170 patients with primary stage I through III lung adenocarcinoma (LADC) and lung squamous cell carcinoma who underwent complete resection at Tokyo Medical and Dental University was screened for TP53 mutations using panel testing, and association studies between TP53 mutations and clinical data, including histology and postoperative recurrence, were performed. The association between TP53 mutations and postoperative recurrence was validated using data from 604 patients with MSK-IMPACT from The Cancer Genome Atlas. Additional immunohistochemistry for p53 was performed on some subsets of the Tokyo Medical and Dental University population.

Results

Mutations in TP53 were recurrently observed (35.9%; 61 out of 170) in the Tokyo Medical and Dental University cohort. In the histology-stratified analysis, patients with LADC histology showed TP53 mutations that were associated with poor relapse-free survival (log-rank test; P = .020), whereas patients with lung squamous cell carcinoma histology showed TP53 mutations that were not (P = .99). The poor prognosis of TP53 mutation-positive LADCs was validated in The Cancer Genome Atlas-LADC cohort (log-rank test; P = .0065). Additional immunohistochemistry for p53 in patients with LADC histology in the Tokyo Medical and Dental University cohort showed a significant correlation between TP53 mutations and abnormal IHC pattern of p53 (Cramer's correlation coefficient V = 0.67).

Conclusions

TP53 mutation is a potential marker for worse prognosis in surgically resected LADC; immunohistochemistry for p53 could be a surrogate method to identify patients with LADC with a worse prognosis.

Inter-equipment validation of PET-based radiomics for predicting EGFR mutation statuses in patients with non-small cell lung cancer

AIM

To validate the inter-equipment generality of the radiomics based on PET images to predict the EGFR mutation status of patients with non-small cell lung cancer.

MATERIALS AND METHODS

Patients were retrospectively collected in the departments of nuclear medicine of Heyi branch (Siemens equipment) and East branch (General Electric (GE) equipment) of the first affiliated hospital of Zhengzhou university. 5 predicting logistic regression models were established. The 1st one was trained and tested by the GE dataset; The 2nd one was trained and tested by the Siemens dataset; The 3rd one was trained and tested by the mixed dataset consisting of GE and Siemens. The 4th one was trained by GE and tested by Siemens; The 5th one was trained by Siemens and tested by GE.

RESULTS

For the 1st ∼ 5th models, the mean values of AUCs for training/testing datasets were 0.78/0.73, 0.74/0.72, 0.75/0.70, 0.74/0.65 and 0.68/0.63, respectively.

CONCLUSION

The AUCs of the models trained and tested on the datasets from the same equipment were higher than those for different equipment. The inter-equipment generality of the radiomics was not good enough in clinical practice.

Application of computed tomography-based radiomics analysis combined with lung cancer serum tumor markers in the identification of lung squamous cell carcinoma and lung adenocarcinoma

OBJECTIVE

To establish a prediction model of lung cancer classification by computed tomography (CT) radiomics with the serum tumor markers (STM) of lung cancer.

MATERIALS AND METHODS

Two-hundred NSCLC patients were enrolled in our study. Clinical data including age, sex, and STM (squamous cell carcinoma [SCC], neuron-specific enolase [NSE], carcinoembryonic antigen [CEA], pro-gastrin-releasing peptide [PRO-GRP], and cytokeratin 19 fragment [cYFRA21-1]) were collected. A radiomics signature was generated from the training set using the least absolute shrinkage and selection operator (LASSO) algorithm. The risk factors were identified using multivariate logistic regression analysis, and a radiomics nomogram based on the radiomics signature and clinical features was constructed. The capability of the nomogram was evaluated using the training set and validated using the validation set. A correction curve and the Hosmer-Lemeshow test were used to evaluate the predictive performance of the radiomics model for the training and test sets.

RESULTS

Twenty-nine of 1234 radiomics parameters were screened as important factors for establishing the radiomics model. The training (area under the curve [AUC] = 0.925; 95% confidence interval [CI]: 0.885-0.966) and validation sets (AUC = 0.921; 95% CI: 0.854-0.989) showed that the CT radiomics signature, combined with STM, accurately predicted lung squamous cell carcinoma and lung adenocarcinoma. Moreover, the logistic regression model showed good performance based on the Hosmer-Lemeshow test in the training (P = 0.954) and test sets (P = 0.340). Good calibration curve consistency also indicated the good performance of the nomogram.

CONCLUSION

The combination of the CT radiomics signature and lung cancer STM performed well for the pathological classification of NSCLC. Compared with the radiomics signature method, the nomogram based on the radiomics signature and clinical factors had better performance for the differential diagnosis of NSCLC.

Genomic progression for local invasion of cutaneous squamous cell carcinoma from the superficial to the deep portion

Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer. While many treatments exist, our understanding of its genomic progression, especially from the epidermis to the deep dermis, remains limited. This study aims to identify genetic mutations associated with the progression of cSCC into the deep dermis, providing insights into its aggressive behavior and high-risk features. We performed high-depth whole-exome sequencing on 12 cSCC tissues, along with paired normal tissues from six patients, using microdissection techniques. The mutational analysis focused on identifying alterations enriched during cSCC progression. Gene Ontology enrichment analysis, immunohistochemical assays, and external single-cell RNA data were utilized for validation. A total of 8863 non-synonymous somatic mutations were identified in 4092 genes across the superficial and deep portions of cSCCs. Analysis of deep portion mutations revealed a significant correlation with gene ontology biological processes, particularly cell junction organization, and cell-cell adhesion. Clonal mutations in these processes were more prevalent in the deep portions, indicating their impact on the cSCC mutation landscape. Genetic evolution analysis identified 29 causal genes associated with dermal invasion in cSCC. We highlight somatic mutations in cSCC, revealing heterogeneity between superficial and deep regions. Altered genes in cell junction organization and cell-cell adhesion emerged as pivotal in dermal invasion. We identified 29 causal genes primarily in deep tumor regions. Our findings emphasize analyzing multiple tumor regions to capture varied mutational landscapes. These insights advance our understanding of cSCC progression, emphasizing genetic and cellular changes during tumor evolution.

Liquid biopsy for the management of NSCLC patients under osimertinib treatment

Therapeutic management of NSCLC patients is quite challenging as they are mainly diagnosed at a late stage of disease, and they present a high heterogeneous molecular profile. Osimertinib changed the paradigm shift in treatment of EGFR mutant NSCLC patients achieving significantly better clinical outcomes. To date, osimertinib is successfully administered not only as first- or second-line treatment, but also as adjuvant treatment while its efficacy is currently investigated during neoadjuvant treatment or in stage III, unresectable EGFR mutant NSCLC patients. However, resistance to osimertinib may occur due to clonal evolution, under the pressure of the targeted therapy. The utilization of liquid biopsy as a minimally invasive tool provides insight into molecular heterogeneity of tumor clonal evolution and potent resistance mechanisms which may help to develop more suitable therapeutic approaches. Longitudinal monitoring of NSCLC patients through ctDNA or CTC analysis could reveal valuable information about clinical outcomes during osimertinib treatment. Therefore, several guidelines suggest that liquid biopsy in addition to tissue biopsy should be considered as a standard of care in the advanced NSCLC setting. This practice could significantly increase the number of NSCLC patients that will eventually benefit from targeted therapies, such as EGFR TKIs.

Signaling dynamics in coexisting monoclonal cell subpopulations unveil mechanisms of resistance to anti-cancer compounds

BACKGROUND

Tumor heterogeneity is a main contributor of resistance to anti-cancer targeted agents though it has proven difficult to study. Unfortunately, model systems to functionally characterize and mechanistically study dynamic responses to treatment across coexisting subpopulations of cancer cells remain a missing need in oncology.

METHODS

Using single cell cloning and expansion techniques, we established monoclonal cell subpopulations (MCPs) from a commercially available epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer cell line. We then used this model sensitivity to the EGFR inhibitor osimertinib across coexisting cell populations within the same tumor. Pathway-centered signaling dynamics associated with response to treatment and morphological characteristics of the MCPs were assessed using Reverse Phase Protein Microarray. Signaling nodes differentially activated in MCPs less sensitive to treatment were then pharmacologically inhibited to identify target signaling proteins putatively implicated in promoting drug resistance.

RESULTS

MCPs demonstrated highly heterogeneous sensitivities to osimertinib. Cell viability after treatment increased > 20% compared to the parental line in selected MCPs, whereas viability decreased by 75% in other MCPs. Reduced treatment response was detected in MCPs with higher proliferation rates, EGFR L858R expression, activation of EGFR binding partners and downstream signaling molecules, and expression of epithelial-to-mesenchymal transition markers. Levels of activation of EGFR binding partners and MCPs' proliferation rates were also associated with response to c-MET and IGFR inhibitors.

CONCLUSIONS

MCPs represent a suitable model system to characterize heterogeneous biomolecular behaviors in preclinical studies and identify and functionally test biological mechanisms associated with resistance to targeted therapeutics.

Multi-omics analysis unveils immunosuppressive microenvironment in the occurrence and development of multiple pulmonary lung cancers

Multiple pulmonary lung cancers (MPLCs) are frequently encountered on computed tomography (CT) scanning of chest, yet their intrinsic characteristics associated with genomic features and radiological or pathological textures that may lead to distinct clinical outcomes remain largely unexplored. A total of 27 pulmonary nodules covering different radiological or pathological textures as well as matched adjacent normal tissues and blood samples were collected from patients diagnosed with MPLCs. Whole-exome sequencing (WES) and whole-transcriptome sequencing were performed. The molecular and immune features of MPLCs associated with distinct radiological or pathological textures were comprehensively investigated. Genomics analysis unveiled the distinct branches of pulmonary nodules originating independently within the same individual. EGFR and KRAS mutations were found to be prevalent in MPLCs, exhibiting mutual exclusivity. The group with KRAS mutations exhibited stronger immune signatures compared to the group with EGFR mutations. Additionally, MPLCs exhibited a pronounced immunosuppressive microenvironment, which was particularly distinct when compared with normal tissues. The expression of the FDSCP gene was specifically observed in MPLCs. When categorizing MPLCs based on radiological or pathological characteristics, a progressive increase in mutation accumulation was observed, accompanied by heightened chromatin-level instability as ground-glass opacity component declined or invasive progression occurred. A close association with the immunosuppressive microenvironment was also observed during the progression of pulmonary nodules. Notably, the upregulation of B cell and regulatory T cell marker genes occurred progressively. Immune cell abundance analysis further demonstrated a marked increase in exhausted cells and regulatory T cells during the progression of pulmonary nodules. These results were further validated by independent datasets including nCounter RNA profiling, single-cell RNA sequencing, and spatial transcriptomic datasets. Our study provided a comprehensive representation of the diverse landscape of MPLCs originating within the same individual and emphasized the significant influence of the immunosuppressive microenvironment in the occurrence and development of pulmonary nodules. These findings hold great potential for enhancing the clinical diagnosis and treatment strategies for MPLCs.

Replication timing alterations are associated with mutation acquisition during breast and lung cancer evolution

During each cell cycle, the process of DNA replication timing is tightly regulated to ensure the accurate duplication of the genome. The extent and significance of alterations in this process during malignant transformation have not been extensively explored. Here, we assess the impact of altered replication timing (ART) on cancer evolution by analysing replication-timing sequencing of cancer and normal cell lines and 952 whole-genome sequenced lung and breast tumours. We find that 6%-18% of the cancer genome exhibits ART, with regions with a change from early to late replication displaying an increased mutation rate and distinct mutational signatures. Whereas regions changing from late to early replication contain genes with increased expression and present a preponderance of APOBEC3-mediated mutation clusters and associated driver mutations. We demonstrate that ART occurs relatively early during cancer evolution and that ART may have a stronger correlation with mutation acquisition than alterations in chromatin structure.

A novel cancer-associated fibroblasts risk score model predict survival and immunotherapy in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide. Cancer-associated fibroblasts (CAFs) are a special type of fibroblasts, which play an important role in the development and immune escape of tumors. Weighted gene co-expression network analysis (WGCNA) was used to construct the co-expression module. In combination with univariate Cox regression and analysis of least absolute shrinkage operator (LASSO), characteristics associated with CAFs were developed for a prognostic model. The migration and proliferation of lung cancer cells were evaluated in vitro. Finally, the expression levels of proteins were analyzed by Western blot. LASSO Cox regression algorithm was then performed to select hub genes. Finally, a total of 2 Genes (COL5A2, COL6A2) were obtained. We then divided LUAD patients into high- and low-risk groups based on CAFs risk scores. Survival analysis, CAFs score correlation analysis and tumor mutation load analysis showed that COL5A2 and COL6A2 were high-risk genes for LUAD. Human Protein Atlas (HPA), western blot and PCR results showed that COL5A2 and COL6A2 were up-regulated in LUAD tissues. When COL5A2 and COL6A2 were knocked down, the proliferation, invasion and migration of lung cancer cells were significantly decreased. Finally, COL5A2 can affect LUAD progression through the Wnt/β-Catenin and TGF-β signaling pathways. Our CAFs risk score model offers a new approach for predicting the prognosis of LUAD patients. Furthermore, the identification of high-risk genes COL5A2 and COL6A2 and drug sensitivity analysis can provide valuable candidate clues for clinical treatment of LUAD.

Transcriptomic Analysis Reveals Early Alterations Associated with Intrinsic Resistance to Targeted Therapy in Lung Adenocarcinoma Cell Lines

Lung adenocarcinoma is the most prevalent form of lung cancer, and drug resistance poses a significant obstacle in its treatment. This study aimed to investigate the overexpression of long non-coding RNAs (lncRNAs) as a mechanism that promotes intrinsic resistance in tumor cells from the onset of treatment. Drug-tolerant persister (DTP) cells are a subset of cancer cells that survive and proliferate after exposure to therapeutic drugs, making them an essential object of study in cancer treatment. The molecular mechanisms underlying DTP cell survival are not fully understood; however, long non-coding RNAs (lncRNAs) have been proposed to play a crucial role. DTP cells from lung adenocarcinoma cell lines were obtained after single exposure to tyrosine kinase inhibitors (TKIs; erlotinib or osimertinib). After establishing DTP cells, RNA sequencing was performed to investigate the differential expression of the lncRNAs. Some lncRNAs and one mRNA were overexpressed in DTP cells. The clinical relevance of lncRNAs was evaluated in a cohort of patients with lung adenocarcinoma from The Cancer Genome Atlas (TCGA). RT-qPCR validated the overexpression of lncRNAs and mRNA in the residual DTP cells and LUAD biopsies. Knockdown of these lncRNAs increases the sensitivity of DTP cells to therapeutic drugs. This study provides an opportunity to investigate the involvement of lncRNAs in the genetic and epigenetic mechanisms that underlie intrinsic resistance. The identified lncRNAs and CD74 mRNA may serve as potential prognostic markers or therapeutic targets to improve the overall survival (OS) of patients with lung cancer.

An agent-based modelling framework to study growth mechanisms in EGFR-L858R mutant cell alveolar type II cells

Mutations in the epidermal growth factor receptor (EGFR) are common in non-small cell lung cancer (NSCLC), particularly in never-smoker patients. However, these mutations are not always carcinogenic, and have recently been reported in histologically normal lung tissue from patients with and without lung cancer. To investigate the outcome of EGFR mutation in healthy lung stem cells, we grow murine alveolar type II organoids monoclonally in a three-dimensional Matrigel. Our experiments show that the EGFR-L858R mutation induces a change in organoid structure: mutated organoids display more 'budding', in comparison with non-mutant controls, which are nearly spherical. We perform on-lattice computational simulations, which suggest that this can be explained by the concentration of division among a small number of cells on the surface of the mutated organoids. We are currently unable to distinguish the cell-based mechanisms that lead to this spatial heterogeneity in growth, but suggest a number of future experiments which could be used to do so. We suggest that the likelihood of L858R-fuelled tumorigenesis is affected by whether the mutation arises in a spatial environment that allows the development of these surface protrusions. These data may have implications for cancer prevention strategies and for understanding NSCLC progression.

Circulating Tumor DNA-Guided De-Escalation Targeted Therapy for Advanced Non-Small Cell Lung Cancer: A Nonrandomized Controlled Trial

Importance

Uninterrupted targeted therapy until disease progression or intolerable toxic effects is currently the routine therapy for advanced non-small cell lung cancer (NSCLC) involving driver gene variations. However, drug resistance is inevitable.

Objective

To assess the clinical feasibility of adaptive de-escalation tyrosine kinase inhibitor (TKI) treatment guided by circulating tumor DNA (ctDNA) for achieving complete remission after local consolidative therapy (LCT) in patients with advanced NSCLC.

Design, Setting, and Participants

This prospective nonrandomized controlled trial was conducted at a single center from June 3, 2020, to July 19, 2022, and included 60 patients with advanced NSCLC with driver variations without radiologically detectable disease after TKI and LCT. The median (range) follow-up time was 19.2 (3.8-29.7) months. Data analysis was conducted from December 15, 2022, to May 10, 2023.

Intervention

Cessation of TKI treatment and follow-up every 3 months. Treatment was restarted in patients with progressive disease (defined by the Response Evaluation Criteria in Solid Tumors 1.1 criteria), detectable ctDNA, or elevated carcinoembryonic antigen (CEA) levels, whichever manifested first, and treatment ceased if all indicators were negative during follow-up surveillance.

Main Outcomes and Measures

Progression-free survival (PFS). Secondary end points were objective response rate, time to next treatment, and overall survival.

Results

Among the total study sample of 60 participants (median [range] age, 55 [21-75] years; 33 [55%] were female), the median PFS was 18.4 (95% CI, 12.6-24.2) months and the median (range) total treatment break duration was 9.1 (1.5-28.1) months. Fourteen patients (group A) remained in TKI cessation with a median (range) treatment break duration of 20.3 (6.8-28.1) months; 31 patients (group B) received retreatment owing to detectable ctDNA and/or CEA and had a median PFS of 20.2 (95% CI, 12.9-27.4) months with a median (range) total treatment break duration of 8.8 (1.5-20.6) months; and 15 patients (group C) who underwent retreatment with TKIs due to progressive disease had a median PFS of 5.5 (95% CI, 1.5-7.2) months. For all participants, the TKI retreatment response rate was 96%, the median time to next treatment was 29.3 (95% CI, 25.3-35.2) months, and the data for overall survival were immature.

Conclusions and Relevance

The findings of this nonrandomized controlled trial suggest that this adaptive de-escalation TKI strategy for patients with NSCLC is feasible in those with no lesions after LCT and a negative ctDNA test result. This might provide a de-escalation treatment strategy guided by ctDNA for the subset of patients with advanced NSCLC.

Trial Registration

ClinicalTrials.gov Identifier: NCT03046316.

NKX2‑1 copy number alterations are associated with oncogenic, immunological and prognostic remodeling in non‑small cell lung cancer

NK2 homeobox 1 (NKX2-1) copy number alterations (CNAs) are frequently observed in lung cancer. However, little is known about the complete landscape of focal alterations in NKX2-1 copy number (CN), their clinical significance and their therapeutic implications in non-small cell lung cancer (NSCLC). The correlations between NKX2-1 expression and EGFR driver mutations and programmed death ligand 1 (PD-L1) co-expression were studied using immunohistochemistry and PCR from the tumors of recruited Filipino patients (n=45). Clinical features of NSCLC with NKX2-1 CNAs were resolved at the tumor and clonal levels using the molecular profiles of patients with lung adenocarcinoma and lung squamous cell carcinoma from The Cancer Genome Atlas (n=1,130), and deconvoluted single-cell RNA-seq data from the Bivona project (n=1,654), respectively. Despite a significant and positive correlation between expression and CN (r=0.264; P<0.001), NKX2-1 CNAs exerted a stronger influence on the combined EGFR and PD-L1 status of NSCLC tumors than expression. NKX2-1 CN gain was prognostic of favorable survival (P=0.018) and a better response to targeted therapy. NKX2-1 CN loss predicted a worse survival (P=0.041). Mutational architecture in the Y-chromosome differentiated the two prognostic groups. There were 19,941 synonymous mutations and 1,408 genome-wide CN perturbations associated with NKX2-1 CNAs. Tumors with NKX2-1 CN gain expressed lymphocyte markers more heterogeneously than those with CN loss. Higher expression of tumor-infiltrating lymphocyte gene signatures in CN gain was prognostic of longer disease-free survival (P=0.005). Tumors with NKX2-1 CN gain had higher B-cell (P<0.001) and total T-cell estimates (P=0.003). NKX2-1 CN loss was associated with immunologically colder tumors due to higher M2 macrophage infiltrates (P=0.011) and higher expression of immune checkpoint proteins, CD274 (P=0.025), VTCN1 (P<0.001) and LGALS9 (P=0.002). In conclusion, NKX2-1 CNAs are associated with tumors that exhibit clinically diverse characteristics, and with unique oncogenic, immunological and prognostic signatures.

Spatial intratumor heterogeneity of programmed death-ligand 1 expression predicts poor prognosis in resected non-small cell lung cancer

BACKGROUND

We quantified the pathological spatial intratumor heterogeneity of programmed death-ligand 1 (PD-L1) expression and investigated its relevance to patient outcomes in surgically resected non-small cell lung carcinoma (NSCLC).

METHODS

This study enrolled 239 consecutive surgically resected NSCLC specimens of pathological stage IIA-IIIB. To characterize the spatial intratumor heterogeneity of PD-L1 expression in NSCLC tissues, we developed a mathematical model based on texture image analysis and determined the spatial heterogeneity index of PD-L1 for each tumor. The correlation between the spatial heterogeneity index of PD-L1 values and clinicopathological characteristics, including prognosis, was analyzed. Furthermore, an independent cohort of 70 cases was analyzed for model validation.

RESULTS

Clinicopathological analysis showed correlations between high spatial heterogeneity index of PD-L1 values and histological subtype (squamous cell carcinoma; P < .001) and vascular invasion (P = .004). Survival analysis revealed that patients with high spatial heterogeneity index of PD-L1 values presented a significantly worse recurrence-free rate than those with low spatial heterogeneity index of PD-L1 values (5-year recurrence-free survival [RFS] = 26.3% vs 47.1%, P < .005). The impact of spatial heterogeneity index of PD-L1 on cancer survival rates was verified through validation in an independent cohort. Additionally, high spatial heterogeneity index of PD-L1 values were associated with tumor recurrence in squamous cell carcinoma (5-year RFS = 29.2% vs 52.8%, P < .05) and adenocarcinoma (5-year RFS = 19.6% vs 43.0%, P < .01). Moreover, we demonstrated that a high spatial heterogeneity index of PD-L1 value was an independent risk factor for tumor recurrence.

CONCLUSIONS

We presented an image analysis model to quantify the spatial intratumor heterogeneity of protein expression in tumor tissues. This model demonstrated that the spatial intratumor heterogeneity of PD-L1 expression in surgically resected NSCLC predicts poor patient outcomes.

ROS1 fusions in resected stage I-III adenocarcinoma: Results from the European Thoracic Oncology Platform Lungscape project

BACKGROUND

ROS1 fusion is a relatively low prevalence (0.6-2.0%) but targetable driver in lung adenocarcinoma (LUAD). Robust and low-cost tests, such as immunohistochemistry (IHC), are desirable to screen for patients potentially harboring this fusion. The aim was to investigate the prevalence of ROS1 fusions in a clinically annotated European stage I-III LUAD cohort using IHC screening with the in vitro diagnostics (IVD)-marked clone SP384, followed by confirmatory molecular analysis in pre-defined subsets.

METHODS

Resected LUADs constructed in tissue microarrays, were immunostained for ROS1 expression using SP384 clone in a ready-to-use kit and Ventana immunostainers. After external quality control, analysis was performed by trained pathologists. Staining intensity of at least 2+ (any percentage of tumor cells) was considered IHC positive (ROS1 IHC + ). Subsequently, ROS1 IHC + cases were 1:1:1 matched with IHC0 and IHC1 + cases and subjected to orthogonal ROS1 FISH and RNA-based testing.

RESULTS

The prevalence of positive ROS1 expression (ROS1 IHC + ), defined as IHC 2+/3+, was 4 % (35 of 866 LUADs). Twenty-eight ROS1 IHC + cases were analyzed by FISH/RNA-based testing, with only two harboring a confirmed ROS1 gene fusion, corresponding to a lower limit for the prevalence of ROS1 gene fusion of 0.23 %. They represent a 7 % probability of identifying a fusion among ROS1 IHC + cases. Both confirmed cases were among the only four with sufficient material and H-score ≥ 200, leading to a 50 % probability of identifying a ROS1 gene fusion in cases with an H-score considered strongly positive. All matched ROS1 IHC- (IHC0 and IHC1 + ) cases were also found negative by FISH/RNA-based testing, leading to a 100 % probability of lack of ROS1 fusion for ROS1 IHC- cases.

CONCLUSIONS

The prevalence of ROS1 fusion in an LUAD stage I-III European cohort was relatively low. ROS1 IHC using SP384 clone is useful for exclusion of ROS1 gene fusion negative cases.

Frequency-dependent selection of neoantigens fosters tumor immune escape and predicts immunotherapy response

Cancer is an evolutionary process shaped by selective pressure from the microenvironments. However, recent studies reveal that certain tumors undergo neutral evolution where there is no detectable fitness difference amongst the cells following malignant transformation. Here, through computational modeling, we demonstrate that negative frequency-dependent selection (or NFDS), where the immune response against cancer cells depends on the clonality of neoantigens, can lead to an immunogenic landscape that is highly similar to neutral evolution. Crucially, NFDS promotes high antigenic heterogeneity and early immune evasion in hypermutable tumors, leading to poor responses to immune checkpoint blockade (ICB) therapy. Our model also reveals that NFDS is characterized by a negative association between average clonality and total burden of neoantigens. Indeed, this unique feature of NFDS is common in the whole-exome sequencing (WES) datasets (357 tumor samples from 275 patients) from four melanoma cohorts with ICB therapy and a non-small cell lung cancer (NSCLC) WES dataset (327 tumor samples from 100 patients). Altogether, our study provides quantitative evidence supporting the theory of NFDS in cancer, explaining the high prevalence of neutral-looking tumors. These findings also highlight the critical role of frequency-dependent selection in devising more efficient and predictive immunotherapies.

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.

Spatial heterogeneity in tumor adhesion qualifies collective cell invasion

Collective cell invasion (CCI), a canon of most invasive solid tumors, is an emergent property of the interactions between cancer cells and their surrounding extracellular matrix (ECM). However, tumor populations invariably consist of cells expressing variable levels of adhesive proteins that mediate such interactions, disallowing an intuitive understanding of how tumor invasiveness at a multicellular scale is influenced by spatial heterogeneity of cell-cell and cell-ECM adhesion. Here, we have used a Cellular Potts model-based multiscale computational framework that is constructed on the histopathological principles of glandular cancers. In earlier efforts on homogenous cancer cell populations, this framework revealed the relative ranges of interactions, including cell-cell and cell-ECM adhesion that drove collective, dispersed, and mixed multimodal invasion. Here, we constitute a tumor core of two separate cell subsets showing distinct intra- and inter-subset cell-cell or cell-ECM adhesion strengths. These two subsets of cells are arranged to varying extents of spatial intermingling, which we call the heterogeneity index (HI). We observe that low and high inter-subset cell adhesion favors invasion of high-HI and low-HI intermingled populations with distinct intra-subset cell-cell adhesion strengths, respectively. In addition, for explored values of cell-ECM adhesion strengths, populations with high HI values collectively invade better than those with lower HI values. We then asked how spatial invasion is regulated by progressively intermingled cellular subsets that are epithelial, i.e., showed high cell-cell but poor cell-ECM adhesion, and mesenchymal, i.e., with reversed adhesion strengths to the former. Here too, inter-subset adhesion plays an important role in contextualizing the proportionate relationship between HI and invasion. An exception to this relationship is seen for cases of heterogeneous cell-ECM adhesion where sub-maximal HI patterns with higher outer localization of cells with stronger ECM adhesion collectively invade better than their relatively higher-HI counterparts. Our simulations also reveal how adhesion heterogeneity qualifies collective invasion, when either cell-cell or cell-ECM adhesion type is varied but results in an invasive dispersion when both adhesion types are simultaneously altered.

Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX

The growing scale and dimensionality of multiplexed imaging require reproducible and comprehensive yet user-friendly computational pipelines. TRACERx-PHLEX performs deep learning-based cell segmentation (deep-imcyto), automated cell-type annotation (TYPEx) and interpretable spatial analysis (Spatial-PHLEX) as three independent but interoperable modules. PHLEX generates single-cell identities, cell densities within tissue compartments, marker positivity calls and spatial metrics such as cellular barrier scores, along with summary graphs and spatial visualisations. PHLEX was developed using imaging mass cytometry (IMC) in the TRACERx study, validated using published Co-detection by indexing (CODEX), IMC and orthogonal data and benchmarked against state-of-the-art approaches. We evaluated its use on different tissue types, tissue fixation conditions, image sizes and antibody panels. As PHLEX is an automated and containerised Nextflow pipeline, manual assessment, programming skills or pathology expertise are not essential. PHLEX offers an end-to-end solution in a growing field of highly multiplexed data and provides clinically relevant insights.

Oncogene-Driven Non-Small Cell Lung Cancers in Patients with a History of Smoking Lack Smoking-Induced Mutations

Non-small cell lung cancers (NSCLC) in nonsmokers are mostly driven by mutations in the oncogenes EGFR, ERBB2, and MET and fusions involving ALK and RET. In addition to occurring in nonsmokers, alterations in these "nonsmoking-related oncogenes" (NSRO) also occur in smokers. To better understand the clonal architecture and genomic landscape of NSRO-driven tumors in smokers compared with typical-smoking NSCLCs, we investigated genomic and transcriptomic alterations in 173 tumor sectors from 48 NSCLC patients. NSRO-driven NSCLCs in smokers and nonsmokers had similar genomic landscapes. Surprisingly, even in patients with prominent smoking histories, the mutational signature caused by tobacco smoking was essentially absent in NSRO-driven NSCLCs, which was confirmed in two large NSCLC data sets from other geographic regions. However, NSRO-driven NSCLCs in smokers had higher transcriptomic activities related to the regulation of the cell cycle. These findings suggest that, whereas the genomic landscape is similar between NSRO-driven NSCLC in smokers and nonsmokers, smoking still affects the tumor phenotype independently of genomic alterations.

SIGNIFICANCE

Non-small cell lung cancers driven by nonsmoking-related oncogenes do not harbor genomic scars caused by smoking regardless of smoking history, indicating that the impact of smoking on these tumors is mainly nongenomic.

Decoding temporal heterogeneity in NSCLC through machine learning and prognostic model construction

BACKGROUND

Non-small cell lung cancer (NSCLC) is a prevalent and heterogeneous disease with significant genomic variations between the early and advanced stages. The identification of key genes and pathways driving NSCLC tumor progression is critical for improving the diagnosis and treatment outcomes of this disease.

METHODS

In this study, we conducted single-cell transcriptome analysis on 93,406 cells from 22 NSCLC patients to characterize malignant NSCLC cancer cells. Utilizing cNMF, we classified these cells into distinct modules, thus identifying the diverse molecular profiles within NSCLC. Through pseudotime analysis, we delineated temporal gene expression changes during NSCLC evolution, thus demonstrating genes associated with disease progression. Using the XGBoost model, we assessed the significance of these genes in the pseudotime trajectory. Our findings were validated by using transcriptome sequencing data from The Cancer Genome Atlas (TCGA), supplemented via LASSO regression to refine the selection of characteristic genes. Subsequently, we established a risk score model based on these genes, thus providing a potential tool for cancer risk assessment and personalized treatment strategies.

RESULTS

We used cNMF to classify malignant NSCLC cells into three functional modules, including the metabolic reprogramming module, cell cycle module, and cell stemness module, which can be used for the functional classification of malignant tumor cells in NSCLC. These findings also indicate that metabolism, the cell cycle, and tumor stemness play important driving roles in the malignant evolution of NSCLC. We integrated cNMF and XGBoost to select marker genes that are indicative of both early and advanced NSCLC stages. The expression of genes such as CHCHD2, GAPDH, and CD24 was strongly correlated with the malignant evolution of NSCLC at the single-cell data level. These genes have been validated via histological data. The risk score model that we established (represented by eight genes) was ultimately validated with GEO data.

CONCLUSION

In summary, our study contributes to the identification of temporal heterogeneous biomarkers in NSCLC, thus offering insights into disease progression mechanisms and potential therapeutic targets. The developed workflow demonstrates promise for future applications in clinical practice.

Mixed responses to targeted therapy driven by chromosomal instability through p53 dysfunction and genome doubling

The phenomenon of mixed/heterogenous treatment responses to cancer therapies within an individual patient presents a challenging clinical scenario. Furthermore, the molecular basis of mixed intra-patient tumor responses remains unclear. Here, we show that patients with metastatic lung adenocarcinoma harbouring co-mutations of EGFR and TP53, are more likely to have mixed intra-patient tumor responses to EGFR tyrosine kinase inhibition (TKI), compared to those with an EGFR mutation alone. The combined presence of whole genome doubling (WGD) and TP53 co-mutations leads to increased genome instability and genomic copy number aberrations in genes implicated in EGFR TKI resistance. Using mouse models and an in vitro isogenic p53-mutant model system, we provide evidence that WGD provides diverse routes to drug resistance by increasing the probability of acquiring copy-number gains or losses relative to non-WGD cells. These data provide a molecular basis for mixed tumor responses to targeted therapy, within an individual patient, with implications for therapeutic strategies.

Molecular landscape and multi-omic measurements of heterogeneity in fetal adenocarcinoma of the lung

Fetal adenocarcinoma of the lung (FLAC) is a rare form of lung adenocarcinoma and was divided into high-grade (H-FLAC) and low-grade (L-FLAC) subtypes. Despite the existence of some small case series studies, a comprehensive multi-omics study of FLAC has yet to be undertaken. In this study, we depicted the multi-omics landscapes of this rare lung cancer type by performing multi-regional sampling on 20 FLAC cases. A comparison of multi-omics profiles revealed significant differences between H-FLAC and L-FLAC in a multi-omic landscape. Two subtypes also showed distinct relationships between multi-layer intratumor heterogeneity (ITH). We discovered that a lower genetic ITH was significantly associated with worse recurrence-free survival and overall survival in FLAC patients, whereas higher methylation ITH in H-FLAC patients suggested a short survival. Our findings highlight the complex interplay between genetic and transcriptional heterogeneity in FLAC and suggest that different types of ITH may have distinct implications for patient prognosis.

Genetic profiles of oligometastatic non-small-cell lung cancer and corresponding brain metastases

OBJECTIVES

In patients with oligometastatic non-small-cell lung cancer (NSCLC), systemic therapy in combination with local ablative treatment of the primary tumour and all metastatic sites is associated with improved prognosis. For patient selection and treatment allocation, further knowledge about the molecular characteristics of the oligometastatic state is necessary. Here, we performed a genetic characterization of primary NSCLC and corresponding brain metastases (BM).

METHODS

We retrospectively identified patients with oligometastatic NSCLC and synchronous (<3 months) or metachronous (>3 months) BM who underwent surgical resection of both primary tumour and BM. Mutation profiling of formalin-fixed paraffin-embedded tumour cell blocks was performed by targeted next-generation sequencing using the Oncomine Focus Assay panel.

RESULTS

Sequencing was successful in 46 paired samples. An oncogenic alteration was present in 31 primary tumours (67.4%) and 40 BM (86.9%). The alteration of the primary tumours was preserved in the corresponding BM in 29 out of 31 cases (93.5%). The most prevalent oncogenic driver in both primary tumours and BM was a KRAS (Kirsten rat sarcoma viral oncogene) mutation (s = 21). In 16 patients (34.8%), the BM harboured additional oncogenic alterations. The presence of a private genetic alteration in the BM was an independent predictor of shorter overall survival.

CONCLUSIONS

In oligometastatic NSCLC, BM retain the main genetic alterations of the primary tumours. Patients may profit from targeted inhibition of mutated KRAS. Additional private genetic alterations in the BM are dismal.

Spatial Architecture of Myeloid and T Cells Orchestrates Immune Evasion and Clinical Outcome in Lung Cancer

Understanding the role of the tumor microenvironment (TME) in lung cancer is critical to improving patient outcomes. We identified four histology-independent archetype TMEs in treatment-naïve early-stage lung cancer using imaging mass cytometry in the TRACERx study (n = 81 patients/198 samples/2.3 million cells). In immune-hot adenocarcinomas, spatial niches of T cells and macrophages increased with clonal neoantigen burden, whereas such an increase was observed for niches of plasma and B cells in immune-excluded squamous cell carcinomas (LUSC). Immune-low TMEs were associated with fibroblast barriers to immune infiltration. The fourth archetype, characterized by sparse lymphocytes and high tumor-associated neutrophil (TAN) infiltration, had tumor cells spatially separated from vasculature and exhibited low spatial intratumor heterogeneity. TAN-high LUSC had frequent PIK3CA mutations. TAN-high tumors harbored recently expanded and metastasis-seeding subclones and had a shorter disease-free survival independent of stage. These findings delineate genomic, immune, and physical barriers to immune surveillance and implicate neutrophil-rich TMEs in metastasis.

SIGNIFICANCE

This study provides novel insights into the spatial organization of the lung cancer TME in the context of tumor immunogenicity, tumor heterogeneity, and cancer evolution. Pairing the tumor evolutionary history with the spatially resolved TME suggests mechanistic hypotheses for tumor progression and metastasis with implications for patient outcome and treatment. This article is featured in Selected Articles from This Issue, p. 897.

Spatial genomic, biochemical and cellular mechanisms underlying meningioma heterogeneity and evolution

Intratumor heterogeneity underlies cancer evolution and treatment resistance, but targetable mechanisms driving intratumor heterogeneity are poorly understood. Meningiomas are the most common primary intracranial tumors and are resistant to all medical therapies, and high-grade meningiomas have significant intratumor heterogeneity. Here we use spatial approaches to identify genomic, biochemical and cellular mechanisms linking intratumor heterogeneity to the molecular, temporal and spatial evolution of high-grade meningiomas. We show that divergent intratumor gene and protein expression programs distinguish high-grade meningiomas that are otherwise grouped together by current classification systems. Analyses of matched pairs of primary and recurrent meningiomas reveal spatial expansion of subclonal copy number variants associated with treatment resistance. Multiplexed sequential immunofluorescence and deconvolution of meningioma spatial transcriptomes using cell types from single-cell RNA sequencing show decreased immune infiltration, decreased MAPK signaling, increased PI3K-AKT signaling and increased cell proliferation, which are associated with meningioma recurrence. To translate these findings to preclinical models, we use CRISPR interference and lineage tracing approaches to identify combination therapies that target intratumor heterogeneity in meningioma cell co-cultures.

The yin and yang of chromosomal instability in prostate cancer

Metastatic prostate cancer remains an incurable lethal disease. Studies indicate that prostate cancer accumulates genomic changes during disease progression and displays the highest levels of chromosomal instability (CIN) across all types of metastatic tumours. CIN, which refers to ongoing chromosomal DNA gain or loss during mitosis, and derived aneuploidy, are known to be associated with increased tumour heterogeneity, metastasis and therapy resistance in many tumour types. Paradoxically, high CIN levels are also proposed to be detrimental to tumour cell survival, suggesting that cancer cells must develop adaptive mechanisms to ensure their survival. In the context of prostate cancer, studies indicate that CIN has a key role in disease progression and might also offer a therapeutic vulnerability that can be pharmacologically targeted. Thus, a comprehensive evaluation of the causes and consequences of CIN in prostate cancer, its contribution to aggressive advanced disease and a better understanding of the acquired CIN tolerance mechanisms can translate into new tumour classifications, biomarker development and therapeutic strategies.

A liquid biopsy assay for the noninvasive detection of lymph node metastases in T1 lung adenocarcinoma

INTRODUCTION

Lung adenocarcinoma (LUAD) is a common pathological type of lung cancer. The presence of lymph node metastasis plays a crucial role in determining the overall treatment approach and long-term prognosis for early LUAD, therefore accurate prediction of lymph node metastasis is essential to guide treatment decisions and ultimately improve patient outcomes.

METHODS

We performed transcriptome sequencing on T1 LUAD patients with positive or negative lymph node metastases and combined this data with The Cancer Genome Atlas Program cohort to identify potential risk molecules at the tissue level. Subsequently, by detecting the expression of these risk molecules by real-time quantitative PCR in serum samples, we developed a model to predict the risk of lymph node metastasis from a training cohort of 96 patients and a validation cohort of 158 patients.

RESULTS

Through transcriptome sequencing analysis of tissue samples, we identified 11 RNA (miR-412, miR-219, miR-371, FOXC1, ID1, MMP13, COL11A1, PODXL2, CXCL13, SPOCK1 and MECOM) associated with positive lymph node metastases in T1 LUAD. As the expression of FOXC1 and COL11A1 was not detected in serum, we constructed a predictive model that accurately identifies patients with positive lymph node metastases using the remaining nine RNA molecules in the serum of T1 LUAD patients. In the training set, the model achieved an area under the curve (AUC) of 0.89, and in the validation set, the AUC was 0.91.

CONCLUSIONS

We have established a new risk prediction model using serum samples from T1 LUAD patients, enabling noninvasive identification of those with positive lymph node metastases.

MRI-based parameters and clinical risk factors to predict lymph node metastasis in patients with ypT0 rectal cancer after neoadjuvant chemoradiotherapy

BACKGROUNDS

The aim of this study was to assess the significant risk factors that predict lymph node metastasis in ypT0 patients with locally advanced rectal cancer following chemoradiotherapy (CRT). Additionally, the study aimed to identify high-risk groups who would not be suitable candidates for a rectal-preserving strategy, despite achieving a complete tumour response.

METHODS

Between 2013 and 2021, 226 ypT0 patients with stages II/III rectal cancer underwent CRT and radical surgery were enrolled. Two groups of patients were evaluated: those with lymph nodes metastasis and those without. The selection of variables for multivariable logistic regression was conducted through bivariate logistic regression analysis. Furthermore, the determination of optimal cutoff values for risk factors was achieved using ROC curve analysis.

RESULTS

Nearly 8% (18/226) of patients with ypT0 had positive lymph nodes (LN) on final pathology. Four variables resulted as being independent factors of LN metastasis: pre-CRT tumour movability (OR = 8.618, P = 0.003), pre-CRT maximal LN size (OR = 28.474, P = 0.004), post-CRT tumour vertical length (OR = 1.492, P = 0.050), post-CRT anaemia (OR = 10.288, P = 0.001). The optimal cutoff point of pre-CRT maximal LN size and post-CRT tumour vertical length was 7.50 mm and 3.05 cm, respectively.

CONCLUSION

The prevalence of lymph node metastasis remains at 8% among patients who achieve pathological complete regression of the primary tumour. In instances where patients are considered appropriate candidates for a rectal-preserving strategy after clinical complete remission, careful consideration should be given to the selection of this strategy if specific risk factors are present. These risk factors encompass a maximal LN size surpassing 7.50 mm prior to CRT, a fixed tumour prior to CRT, a tumour vertical length exceeding 3.05 cm after CRT, and the existence of anaemia subsequent to CRT.

"On/off"-switchable crosslinked PTX-nanoformulation with improved precise delivery for NSCLC brain metastases and restrained adverse reaction over nab-PTX

Non-small cell lung cancer (NSCLC) brain metastases present a significant treatment challenge due to limited drug delivery efficiency and severe adverse reactions. In this study, we address these challenges by designing a "on/off" switchable crosslinked paclitaxel (PTX) nanocarrier, BPM-PD, with novel ultra-pH-sensitive linkages (pH 6.8 to 6.5). BPM-PD demonstrates a distinct "on/off" switchable release of the anti-cancer drug paclitaxel (PTX) in response to the acidic extratumoral microenvironment. The "off" state of BPM-PD@PTX effectively prevents premature drug release in the blood circulation, blood-brain barrier (BBB)/blood-tumor barrier (BTB), and normal brain tissue, surpassing the clinical PTX-nanoformulation (nab-PTX). Meanwhile, the "on" state facilitates precise delivery to NSCLC brain metastases cells. Compared to nab-PTX, BPM-PD@PTX demonstrates improved therapeutic efficacy with a reduced tumor area (only 14.6%) and extended survival duration, while mitigating adverse reactions (over 83.7%) in aspartate aminotransferase (AST) and alanine aminotransferase (ALT), offering a promising approach for the treatment of NSCLC brain metastases. The precise molecular switch also helped to increase the PTX maximum tolerated dose from 25 mg/kg to 45 mg/kg This research contributes to the field of cancer therapeutics and has significant implications for improving the clinical outcomes of NSCLC patients.

Integrative Single Cell Atlas Revealed Intratumoral Heterogeneity Generation from an Adaptive Epigenetic Cell State in Human Bladder Urothelial Carcinoma

Intratumor heterogeneity (ITH) of bladder cancer (BLCA) contributes to therapy resistance and immune evasion affecting clinical prognosis. The molecular and cellular mechanisms contributing to BLCA ITH generation remain elusive. It is found that a TM4SF1-positive cancer subpopulation (TPCS) can generate ITH in BLCA, evidenced by integrative single cell atlas analysis. Extensive profiling of the epigenome and transcriptome of all stages of BLCA revealed their evolutionary trajectories. Distinct ancestor cells gave rise to low-grade noninvasive and high-grade invasive BLCA. Epigenome reprograming led to transcriptional heterogeneity in BLCA. During early oncogenesis, epithelial-to-mesenchymal transition generated TPCS. TPCS has stem-cell-like properties and exhibited transcriptional plasticity, priming the development of transcriptionally heterogeneous descendent cell lineages. Moreover, TPCS prevalence in tumor is associated with advanced stage cancer and poor prognosis. The results of this study suggested that bladder cancer interacts with its environment by acquiring a stem cell-like epigenomic landscape, which might generate ITH without additional genetic diversification.

Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

Patient-derived xenograft (PDX) models are widely used in cancer research. To investigate the genomic fidelity of non-small cell lung cancer PDX models, we established 48 PDX models from 22 patients enrolled in the TRACERx study. Multi-region tumor sampling increased successful PDX engraftment and most models were histologically similar to their parent tumor. Whole-exome sequencing enabled comparison of tumors and PDX models and we provide an adapted mouse reference genome for improved removal of NOD scid gamma (NSG) mouse-derived reads from sequencing data. PDX model establishment caused a genomic bottleneck, with models often representing a single tumor subclone. While distinct tumor subclones were represented in independent models from the same tumor, individual PDX models did not fully recapitulate intratumor heterogeneity. On-going genomic evolution in mice contributed modestly to the genomic distance between tumors and PDX models. Our study highlights the importance of considering primary tumor heterogeneity when using PDX models and emphasizes the benefit of comprehensive tumor sampling.

Clinical Applications of Comprehensive Genomic Profiling in Advanced Non-Small-Cell Lung Cancer-A Case Series

BACKGROUND

Advanced non-small-cell lung cancer (NSCLC) can be treated with novel targeted therapies that are tailored to the genetic characteristics of malignancy. While tissue-based genomic testing is considered the gold standard for the detection of oncogenic driver mutations, several challenges like inadequate tissue availability, the invasiveness of procuring tumors, and prolonged turnaround time of analysis are encountered. Considering these limitations, guidelines have recognized liquid biopsies using circulating cell-free DNA (cfDNA) as a useful tool to complement conventional tissue testing. Even though cfDNA next-generation sequencing (NGS) can have high sensitivity and specificity, optimal patient benefit requires the interpretation of the molecular profiling results in the context of clinical and diagnostic features to achieve the best outcomes.

CASE DESCRIPTIONS

In this case series, we present six patients with advanced NSCLC whose plasma or tissue biopsy samples were analyzed with commercially available comprehensive NGS assays that elucidate the role of testing at various time points in the treatment journey. In all six cases, comprehensive genomic profiling (CGP) provided clinically useful information to guide treatment decisions.

CONCLUSION

Adding to the existing real-world evidence, this case series reinforces that CGP-driven treatment strategies in advanced NSCLC, coupled with other available clinical information, can optimize treatment decisions.

Development of new techniques and clinical applications of liquid biopsy in lung cancer management

Lung cancer is an exceedingly malignant tumor reported as having the highest morbidity and mortality of any cancer worldwide, thus posing a great threat to global health. Despite the growing demand for precision medicine, current methods for early clinical detection, treatment and prognosis monitoring in lung cancer are hampered by certain bottlenecks. Studies have found that during the formation and development of a tumor, molecular substances carrying tumor-related genetic information can be released into body fluids. Liquid biopsy (LB), a method for detecting these tumor-related markers in body fluids, maybe a way to make progress in these bottlenecks. In recent years, LB technology has undergone rapid advancements. Therefore, this review will provide information on technical updates to LB and its potential clinical applications, evaluate its effectiveness for specific applications, discuss the existing limitations of LB, and present a look forward to possible future clinical applications. Specifically, this paper will introduce technical updates from the prospectives of engineering breakthroughs in the detection of membrane-based LB biomarkers and other improvements in sequencing technology. Additionally, it will summarize the latest applications of liquid biopsy for the early detection, diagnosis, treatment, and prognosis of lung cancer. We will present the interconnectedness of clinical and laboratory issues and the interplay of technology and application in LB today.

In silico study of heterogeneous tumour-derived organoid response to CAR T-cell therapy

Chimeric antigen receptor (CAR) T-cell therapy is a promising immunotherapy for treating cancers. This method consists in modifying the patients' T-cells to directly target antigen-presenting cancer cells. One of the barriers to the development of this type of therapies, is target antigen heterogeneity. It is thought that intratumour heterogeneity is one of the leading determinants of therapeutic resistance and treatment failure. While understanding antigen heterogeneity is important for effective therapeutics, a good therapy strategy could enhance the therapy efficiency. In this work we introduce an agent-based model (ABM), built upon a previous ABM, to rationalise the outcomes of different CAR T-cells therapies strategies over heterogeneous tumour-derived organoids. We found that one dose of CAR T-cell therapy should be expected to reduce the tumour size as well as its growth rate, however it may not be enough to completely eliminate it. Moreover, the amount of free CAR T-cells (i.e. CAR T-cells that did not kill any cancer cell) increases as we increase the dosage, and so does the risk of side effects. We tested different strategies to enhance smaller dosages, such as enhancing the CAR T-cells long-term persistence and multiple dosing. For both approaches an appropriate dosimetry strategy is necessary to produce "effective yet safe" therapeutic results. Moreover, an interesting emergent phenomenon results from the simulations, namely the formation of a shield-like structure of cells with low antigen expression. This shield turns out to protect cells with high antigen expression. Finally we tested a multi-antigen recognition therapy to overcome antigen escape and heterogeneity. Our studies suggest that larger dosages can completely eliminate the organoid, however the multi-antigen recognition increases the risk of side effects. Therefore, an appropriate small dosages dosimetry strategy is necessary to improve the outcomes. Based on our results, it is clear that a proper therapeutic strategy could enhance the therapies outcomes. In that direction, our computational approach provides a framework to model treatment combinations in different scenarios and to explore the characteristics of successful and unsuccessful treatments.

Multidimensional biological characteristics of ground glass nodules

The detection rate of ground glass nodules (GGNs) has increased in recent years because of their malignant potential but relatively indolent biological behavior; thus, correct GGN recognition and management has become a research focus. Many scholars have explored the underlying mechanism of the indolent progression of GGNs from several perspectives, such as pathological type, genomic mutational characteristics, and immune microenvironment. GGNs have different major mutated genes at different stages of development; EGFR mutation is the most common mutation in GGNs, and p53 mutation is the most abundant mutation in the invasive stage of GGNs. Pure GGNs have fewer genomic alterations and a simpler genomic profile and exhibit a gradually evolving genomic mutation profile as the pathology progresses. Compared to advanced lung adenocarcinoma, GGN lung adenocarcinoma has a higher immune cell percentage, is under immune surveillance, and has less immune escape. However, as the pathological progression and solid component increase, negative immune regulation and immune escape increase gradually, and a suppressive immune environment is established gradually. Currently, regular computer tomography monitoring and surgery are the main treatment strategies for persistent GGNs. Stereotactic body radiotherapy and radiofrequency ablation are two local therapeutic alternatives, and systemic therapy has been progressively studied for lung cancer with GGNs. In the present review, we discuss the characterization of the multidimensional molecular evolution of GGNs that could facilitate more precise differentiation of such highly heterogeneous lesions, laying a foundation for the development of more effective individualized treatment plans.

HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data

Bulk DNA sequencing of multiple samples from the same tumor is becoming common, yet most methods to infer copy-number aberrations (CNAs) from this data analyze individual samples independently. We introduce HATCHet2, an algorithm to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 extends the earlier HATCHet method by improving identification of focal CNAs and introducing a novel statistic, the minor haplotype B-allele frequency (mhBAF), that enables identification of mirrored-subclonal CNAs. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 10 prostate cancer patients reveals previously unreported mirrored-subclonal CNAs affecting cancer genes.