The evolution of lung cancer and impact of subclonal selection in TRACERx

Exploring evolutionary trajectories in ovarian cancer patients by longitudinal analysis of ctDNA

OBJECTIVES

We analysed whether temporal heterogeneity of ctDNA encodes evolutionary patterns in ovarian cancer.

METHODS

Targeted sequencing of 275 cancer-associated genes was performed in a primary tumor biopsy and in ctDNA of six longitudinal plasma samples from 15 patients, using the Illumina platform.

RESULTS

While there was low overall concordance between the mutational spectrum of the primary tumor biopsies vs. ctDNA, TP53 variants were the most commonly shared somatic alterations. Up to three variant clusters were detected in each tumor biopsy, likely representing predominant clones of the primary tumor, most of them harbouring a TP53 variant. By tracing these clusters in ctDNA, we propose that liquid biopsy may allow to assess the contribution of ancestral clones of the tumor to relapsed abdominal masses, revealing two evolutionary patterns. In pattern#1, clusters detected in the primary tumor biopsy were likely relapse seeding clones, as they contributed a major share to ctDNA at relapse. In pattern#2, similar clusters were present in tumors and ctDNA; however, they were entirely cleared from liquid biopsy after chemotherapy and were undetectable at relapse. ctDNA private variants were present among both patterns, with some of them mirroring subclonal expansions after chemotherapy.

CONCLUSIONS

We demonstrate that tracing the temporal heterogeneity of ctDNA, even below exome scale resolution, deciphers evolutionary trajectories in ovarian cancer. Furthermore, we describe two evolutionary patterns that may help to identify relapse seeding clones for targeted therapy.

Cancer cell - Fibroblast crosstalk via HB-EGF, EGFR, and MAPK signaling promotes the expression of macrophage chemo-attractants in squamous cell carcinoma

Interactions between cells in the tumor microenvironment (TME) shape cancer progression and patient prognosis. To gain insights into how the TME influences cancer outcomes, we derive gene expression signatures indicative of signaling between stromal fibroblasts and cancer cells, and demonstrate their prognostic significance in multiple and independent squamous cell carcinoma cohorts. By leveraging information within the signatures, we discover that the HB-EGF/EGFR/MAPK axis represents a hub of tumor-stroma crosstalk, promoting the expression of CSF2 and LIF and favoring the recruitment of macrophages. Together, these analyses demonstrate the utility of our approach for interrogating the extent and consequences of TME crosstalk.

Overcoming drug-resistant tumors with selection gene drives

Drug resistance is a major hurdle prohibiting effective treatment of many diseases, including cancer. Using model-guided designs, Leighow et al.1 engineered a dual-switch selection gene drive system custom designed to combat drug-resistant tumors. By demonstrating remarkable killing efficacies in preclinical models using human non-small lung cancer cells in vitro and in mice, this work describes an attractive mindset to develop next-generation anticancer therapies.

The evolutionary theory of cancer: challenges and potential solutions

The clonal evolution model of cancer was developed in the 1950s-1970s and became central to cancer biology in the twenty-first century, largely through studies of cancer genetics. Although it has proven its worth, its structure has been challenged by observations of phenotypic plasticity, non-genetic forms of inheritance, non-genetic determinants of clone fitness and non-tree-like transmission of genes. There is even confusion about the definition of a clone, which we aim to resolve. The performance and value of the clonal evolution model depends on the empirical extent to which evolutionary processes are involved in cancer, and on its theoretical ability to account for those evolutionary processes. Here, we identify limits in the theoretical performance of the clonal evolution model and provide solutions to overcome those limits. Although we do not claim that clonal evolution can explain everything about cancer, we show how many of the complexities that have been identified in the dynamics of cancer can be integrated into the model to improve our current understanding of cancer.

Intratumoral heterogeneity of oncogenic drivers in mixed histology lung adenocarcinomas: How tissue selection impacts molecular testing?

Majority of the lung adenocarcinomas show a mixture of different histological patterns. The possibility of histologically heterogeneous areas of the adenocarcinoma showing genetic heterogeneity and harboring different driver mutations, with potentially significant clinical impact, has not been adequately addressed. Currently, there are no guidelines to suggest how to submit tumor tissue in adenocarcinomas with mixed histological features for molecular testing. The objective of this study is to assess intra-tumoral heterogeneity in prominent driver mutations among different morphological patterns of lung adenocarcinoma, its implications on the future of molecular testing as well as its potential impact on patient management. Twenty-three cases of mixed histology lung adenocarcinoma resected between 2018 and 2023 were retrieved from the archives. H&E slides were reviewed to identify the predominant and second most predominant histological patterns. The morphologically different tumor areas were manually macro-dissected for DNA extraction. Next-Generation Sequencing with Ion AmpliSeq™ Cancer Hotspot Panel v2 (Thermo Fisher Scientific, USA). Thirteen cases showed the same pathological variant in both histological components tested. Three cases (13 %) exhibited disparities in the variants detected across the different histological patterns tested (p=0.025). The discrepant findings had a direct therapeutic impact in 4.3 % cases. Seven cases showed no pathogenic variants detected on either of the histological components tested. This study elucidates the presence of infrequent yet significant intra-tumoral heterogeneity in the molecular profiles of mixed histology adenocarcinomas, highlighting the need for guidelines directing tissue selection for molecular testing to avoid missed therapeutic opportunities and mitigate disease relapse.

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.

Targeting chromosomal instability in patients with cancer

Chromosomal instability (CIN) is a hallmark of cancer and a driver of metastatic dissemination, therapeutic resistance, and immune evasion. CIN is present in 60-80% of human cancers and poses a formidable therapeutic challenge as evidenced by the lack of clinically approved drugs that directly target CIN. This limitation in part reflects a lack of well-defined druggable targets as well as a dearth of tractable biomarkers enabling direct assessment and quantification of CIN in patients with cancer. Over the past decade, however, our understanding of the cellular mechanisms and consequences of CIN has greatly expanded, revealing novel therapeutic strategies for the treatment of chromosomally unstable tumours as well as new methods of assessing the dynamic nature of chromosome segregation errors that define CIN. In this Review, we describe advances that have shaped our understanding of CIN from a translational perspective, highlighting both challenges and opportunities in the development of therapeutic interventions for patients with chromosomally unstable cancers.

Multiregion exome sequencing indicates a monoclonal origin of esophageal spindle-cell squamous cell carcinoma

Esophageal spindle-cell squamous cell carcinoma (ESS) is a rare biphasic neoplasm composed of a carcinomatous component (CaC) and a sarcomatous component (SaC). However, the genomic origin and gene signature of ESS remain unclear. Using whole-exome sequencing of laser-capture microdissection (LCM) tumor samples, we determined that CaC and SaC showed high mutational commonality, with the same top high-frequency mutant genes, mutation signatures, and tumor mutation burden; paired samples shared a median of 25.5% mutation sites. Focal gains were found on chromosomes 3q29, 5p15.33, and 11q13.3. Altered genes were mainly enriched in the RTK-RAS signaling pathway. Phylogenetic trees showed a monoclonal origin of ESS. The most frequently mutated oncogene in the trunk was TP53, followed by NFE2L2, KMT2D, and MUC16. Prognostic associations were found for CDC27, LRP2, APC, and SNAPC4. Our data highlight the monoclonal origin of ESS with TP53 as a potent driver oncogene, suggesting new targeted therapies and immunotherapies as treatment options. © 2024 The Pathological Society of Great Britain and Ireland.

Reprogramming hematopoietic stem cell metabolism in lung cancer: glycolysis, oxidative phosphorylation, and the role of 2-DG

Hematopoietic stem cells (HSCs) exhibit significant functional and metabolic alterations within the lung cancer microenvironment, contributing to tumor progression and immune evasion by increasing differentiation into myeloid-derived suppressor cells (MDSCs). Our aim is to analyze the metabolic transition of HSCs from glycolysis to oxidative phosphorylation (OXPHOS) in lung cancer and determine its effects on HSC functionality. Using a murine Lewis Lung Carcinoma lung cancer model, we conducted metabolic profiling of long-term and short-term HSCs, as well as multipotent progenitors, comparing their metabolic states in normal and cancer conditions. We measured glucose uptake using 2-[N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl)Amino]-2-Deoxyglucose (2-NBDG) and assessed levels of lactate, acetyl-coenzyme A, and ATP. Mitochondrial functionality was evaluated through flow cytometry, alongside the impact of the glucose metabolism inhibitor 2-DG on HSC differentiation and mitochondrial activity. HSCs under lung cancer conditions showed increased glucose uptake and lactate production, with an associated rise in OXPHOS activity, marking a metabolic shift. Treatment with 2-DG led to decreased T-HSCs and MDSCs and an increased red blood cell count, highlighting its potential to influence metabolic and differentiation pathways in HSCs. This study provides novel insights into the metabolic reprogramming of HSCs in lung cancer, emphasizing the critical shift from glycolysis to OXPHOS and its implications for the therapeutic targeting of cancer-related metabolic pathways.

Recent advancements in the small-molecule drugs for hepatocellular carcinoma (HCC): Structure-activity relationships, pharmacological activities, and the clinical trials

BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world and the sixth leading cause of cancer death worldwide, and it is urgent to find safe and effective drugs for treatment. As an important therapeutic method, small-molecule drugs are continually being updated to achieve improved therapeutic effects. The purpose of this study was to investigate the structural effects of various FDA-listed small-molecule drugs sorafenib, cabozantinib, lenvatinib, and regorafenib on the corresponding HCC targets and possible structural optimization methods, and to explore the mechanism for identifying potential therapeutic drugs that offer better efficacy and fewer side effects.

METHODS

The structure-activity relationship, pharmacological actions, and clinical applications of small-molecule drugs were reviewed by referencing MEDLINE, Web of Science, CNKI, and other databases, summarizing and integrating the relevant content.

RESULTS

The results showed that small-molecule drugs can inhibit HCC primarily by forming hydrogen bonds with Glu885, Asp1046, and Cys919 on the HCC target. HCC can be targeted by inhibiting the activation of multiple pathways, blocking the conduction of downstream signaling, and reducing the formation of tumor blood vessels. In general, small-molecule drugs primarily target four key receptors in HCC: VEGFR, PDGFR, EGFR, and FGFR, to achieve effective treatment.

CONCLUSIONS

By revealing their structure-activity relationships, pharmacological actions, and clinical trials, small-molecule drugs can offer broad prospects for the development of new medications.

Evolutionary dependency of cancer mutations in gene pairs inferred by nonsynonymous-synonymous mutation ratios

BACKGROUND

Determining the impact of somatic mutations requires understanding the functional relationship of genes acquiring mutations; however, it is largely unknown how mutations in functionally related genes influence each other.

METHODS

We employed non-synonymous-to-synonymous or dNdS ratios to evaluate the evolutionary dependency (ED) of gene pairs, assuming a mutation in one gene of a gene pair can affect the evolutionary fitness of mutations in its partner genes as mutation context. We employed PanCancer- and tumor type-specific mutational profiles to infer the ED of gene pairs and evaluated their biological relevance with respect to gene dependency and drug sensitivity.

RESULTS

We propose that dNdS ratios of gene pairs and their derived cdNS (context-dependent dNdS) scores as measure of ED distinguishing gene pairs either as synergistic (SYN) or antagonistic (ANT). Mutation contexts can induce substantial changes in the evolutionary fitness of mutations in the paired genes, e.g., IDH1 and IDH2 mutation contexts lead to substantial increase and decrease of dNdS ratios of ATRX indels and IDH1 missense mutations corresponding to SYN and ANT relationship with positive and negative cdNS scores, respectively. The impact of gene silencing or knock-outs on cell viability (genetic dependencies) often depends on ED, suggesting that ED can guide the selection of candidates for synthetic lethality such as TCF7L2-KRAS mutations. Using cell line-based drug sensitivity data, the effects of targeted agents on cell lines are often associated with mutations of genes exhibiting ED with the target genes, informing drug sensitizing or resistant mutations for targeted inhibitors, e.g., PRSS1 and CTCF mutations as resistant mutations to EGFR and BRAF inhibitors for lung adenocarcinomas and melanomas, respectively.

CONCLUSIONS

We propose that the ED of gene pairs evaluated by dNdS ratios can advance our understanding of the functional relationship of genes with potential biological and clinical implications.

Synthesis of chitosan polyethylene glycol antibody complex for delivery of Imatinib in lung cancer cell lines

Lung cancer is known as the most common cancer. Although the Ramucirumab antibody is a second-line treatment for lung cancer, the high interstitial fluid pressure limits the antibody's performance. In this way, Imatinib is a chemotherapeutic drug to reduce the interstitial fluid pressure. Up to now, unfortunately, both Ramucirumab and imatinib have not been reported in one nanosystem for cancer therapy. To fulfill this shortcoming, this paper aims to design a chitosan nanocarrier that loads imatinib and attaches to Ramucirumab for selective bonding to A549. Therefore, this paper aims to develop a polymeric nanosystem for non-small cell lung cancer (NSCLC) treatment. In first, the chitosan polyethylene glycol nanoparticle is synthesized, loaded with imatinib, and then targeted using Ramucirumab. Afterwards, the CS-PEG-Ab-Im by FTIR, TEM, DLS, zeta potential, and TGA techniques are characterized. The size of CS-PEG-Ab-Im was 25-30 nm, its surface charge was 13.1 mV, and the shape of CS-PEG-Ab-Im was nearly spherical and cylindrical. The therapeutic potential of CS-PEG-Ab-Im was assessed using the A549 cell line. According to the obtained results, the cell viability was 48% after 48 h of treatment of A549 cells using the IC50 concentration of CS-PEG-Ab-Im (100 nanomolar). Moreover, the apoptosis and cell cycle arrest percentages were increased by 3 and 6 times, respectively, as compared to free imatinib. Furthermore, the release rate of imatinib from CS-PEG-Ab-Im in an acidic medium was 17% during 1 h, indicating five times the imatinib release in the natural medium. Eventually, the result of flow cytometry indicates the more apoptotic effect of nanosystem to free imatinib and CS-PEG-Ab. Besides, cell arresting result exhibits the CS-PEG-Ab-Im and causes cell arrested at G1 by %8.17. Thus, it can be concluded that CS-PEG-Ab-Im can be an ideal nanosystem in NSCLC treatment.

HTR3A Promotes Non-small Cell Lung Cancer Through the FOXH1/Wnt3A Signaling Pathway

5-Hydroxytryptamine receptors (5-HTRs) are strongly correlated with tumor progression in various types of cancer. Despite this, the underlying mechanisms responsible for the role of 5-HTRs in non-small cell lung cancer (NSCLC) remains unclear. This study aimed to investigate the relationship between 5-hydroxytryptamine receptor 3A (HTR3A) and NSCLC development. Our findings indicated a higher distribution of HTR3A expression in NSCLC tissues when compared with normal tissues, where patients with high HTR3A levels demonstrated shorter overall survival times. In vitro analyses revealed that overexpression of HTR3A facilitated the proliferation and migration of NSCLC cell lines (A549 and NCI-H3255). Similarly, a notable acceleration of tumor growth and enhanced pulmonary tumorigenic potential were observed in HTR3A-overexpressing tumor-bearing mice. Mechanistically, upregulation of Forkhead Box H1 (FOXH1) by HTR3A led to the activation of Wnt3A/β-catenin signaling pathways, thereby promoting the development of NSCLC. Our report thus highlights the significance of the HTR3A/FOXH1 axis during tumor progression in NSCLC, proposing HTR3A as a possible diagnostic indicator and candidate target for clinical therapy.

Second Primary Lung Cancer - An Emerging Issue in Lung Cancer Survivors

As a result of an increased focus on early detection including lung cancer screening, combined with more curative treatment options, the 5-year survival rates for lung cancer are improving. Welcome though this is, it brings new, hitherto unseen challenges. As more patients are cured and survive longer, they are at risk of developing second primary cancers, particularly lung cancer. In this review, we examine the challenges that surveillance, diagnosis, and management of second primary lung cancer (SPLC) bring and how these can be addressed. Recent data from prospective follow-up studies suggests that the incidence of SPLC may be higher than previously appreciated, partly due to an increase in multi-focal adenocarcinoma spectrum disease. Over 5 years, up to 1 in 6 long-term lung cancer survivors may develop a SPLC. Although not routinely used in clinical practice at present, genomic approaches for differentiating SPLC from intrapulmonary metastases of the first primary are emerging, and we highlight how this could be used to help differentiate lesions. An accurate distinction between SPLC and the recurrence of the first primary is of paramount importance due to the very different management strategies that may be required. Wrongly classifying an SPLC as a recurrence of the first primary may have significant consequences for patient management and overall survival. Updated approaches to the classification of SPLC combining clinical history, histopathological assessment, and genomic profiling are needed. Finally, we review the potential role of early detection biomarkers in the identification of SPLC, focusing in particular on blood-based biomarkers that are being examined in a multi-center prospective study recruiting lung cancer survivors.

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.

Spatial intra-tumour heterogeneity and treatment-induced genomic evolution in oesophageal adenocarcinoma: implications for prognosis and therapy

BACKGROUND

Oesophageal adenocarcinoma (OAC) is a highly heterogeneous cancer with poor survival. Standard curative treatment is chemotherapy with or without radiotherapy followed by oesophagectomy. Genomic heterogeneity is a feature of OAC and has been linked to treatment resistance.

METHODS

Whole-genome sequencing data from 59 treatment-naïve and 18 post-treatment samples from 29 OAC patients was analysed. Twenty-seven of these were enrolled in the DOCTOR trial, sponsored by the Australasian Gastro-Intestinal Trials Group. Two biopsies from each treatment-naïve tumour were assessed to define 'shared' (between both samples) and 'private' (present in one sample) mutations.

RESULTS

Mutational signatures SBS2/13 (APOBEC) and SBS3 (BRCA) were almost exclusively detected in private mutation populations of treatment-naïve tumours. Patients presenting these signatures had significantly worse disease specific survival. Furthermore, mutational signatures associated with platinum-based chemotherapy treatment as well as high platinum enrichment scores were only detected in post-treatment samples. Additionally, clones with high putative neoantigen binding scores were detected in some treatment-naïve samples suggesting immunoediting of clones.

CONCLUSIONS

This study demonstrates the high intra-tumour heterogeneity in OAC, as well as indicators for treatment-induced changes during tumour evolution. Intra-tumour heterogeneity remains a problem for successful treatment strategies in OAC.

Highly consistency of PIK3CA mutation spectrum between circulating tumor DNA and paired tissue in lung cancer patients

Background

Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha ( PIK3CA) mutations are associated with drug resistance and prognosis in lung cancer; however, the consistency and clinical value of PIK3CA mutations between tissue and liquid samples are unknown.

Methods

Circulating tumor DNA (ctDNA) and matched tumor tissue samples from 405 advanced lung cancer patients were collected at Jilin Cancer Hospital between 2018 and 2022, and the PIK3CA mutation status was sequenced using next-generation sequencing based on a 520 gene panel. The viability of different mutant lung cancer cells was detected using MTT assay.

Results

PIK3CA mutations were detected in 46 (5.68 %) of 810 lung cancer samples, with 21 (5.19 %) of 405 plasma samples and 25 (6.17 %) of 405 matched tissues. p.Glu542Lys, p.Glu545Lys, and p.His1047Arg were the most common mutation types of PIK3CA in both the ctDNA and tissue samples. The concordance of PIK3CA mutations was 97.53 % between ctDNA and matched tissues (kappa: 0.770, P = 0.000), with sensitivity/true positive rate of 72.0 %, specificity/true negative rate of 99.2 %, and negative predictive value and positive predictive value of 0.982 and 0.857, respectively (AUC = 0.856, P = 0.000). Furthermore, the concordance of PIK3CA mutations was 98.26 % in lung adenocarcinoma and 96.43 % in lung squamous cell carcinoma. TP53 and EGFR were the most common concomitant mutations in ctDNA and tissues. Patients with PIK3CA mutations showed a high tumor mutational burden (TMB) (P < 0.001) and a significant correlation between bTMB and tTMB (r = 0.5986, P = 0.0041). For the tPIK3CAmut/ctDNA PIK3CAmut cohort, PI3K pathways alteration was associated with male sex (P = 0.022), old age (P = 0.007), and smoking (P = 0.001); tPIK3CAmut/ctDNA PIK3CAwt patients harbored clinicopathological factors of adenocarcinoma stage IV, with low PS score (≤1) and TMB.

Conclusion

This study showed that ctDNA is highly concordant and sensitive for identifying PIK3CA mutations, suggesting that PIK3CA mutation detection in liquid samples may be an alternative clinical practice for tissues.

Ongoing genome doubling promotes evolvability and immune dysregulation in ovarian cancer

Whole-genome doubling (WGD) is a critical driver of tumor development and is linked to drug resistance and metastasis in solid malignancies. Here, we demonstrate that WGD is an ongoing mutational process in tumor evolution. Using single-cell whole-genome sequencing, we measured and modeled how WGD events are distributed across cellular populations within tumors and associated WGD dynamics with properties of genome diversification and phenotypic consequences of innate immunity. We studied WGD evolution in 65 high-grade serous ovarian cancer (HGSOC) tissue samples from 40 patients, yielding 29,481 tumor cell genomes. We found near-ubiquitous evidence of WGD as an ongoing mutational process promoting cell-cell diversity, high rates of chromosomal missegregation, and consequent micronucleation. Using a novel mutation-based WGD timing method, doubleTime , we delineated specific modes by which WGD can drive tumor evolution: (i) unitary evolutionary origin followed by significant diversification, (ii) independent WGD events on a pre-existing background of copy number diversity, and (iii) evolutionarily late clonal expansions of WGD populations. Additionally, through integrated single-cell RNA sequencing and high-resolution immunofluorescence microscopy, we found that inflammatory signaling and cGAS-STING pathway activation result from ongoing chromosomal instability and are restricted to tumors that remain predominantly diploid. This contrasted with predominantly WGD tumors, which exhibited significant quiescent and immunosuppressive phenotypic states. Together, these findings establish WGD as an evolutionarily 'active' mutational process that promotes evolvability and dysregulated immunity in late stage ovarian cancer.

Programming tumor evolution with selection gene drives to proactively combat drug resistance

Most targeted anticancer therapies fail due to drug resistance evolution. Here we show that tumor evolution can be reproducibly redirected to engineer therapeutic opportunity, regardless of the exact ensemble of pre-existing genetic heterogeneity. We develop a selection gene drive system that is stably introduced into cancer cells and is composed of two genes, or switches, that couple an inducible fitness advantage with a shared fitness cost. Using stochastic models of evolutionary dynamics, we identify the design criteria for selection gene drives. We then build prototypes that harness the selective pressure of multiple approved tyrosine kinase inhibitors and employ therapeutic mechanisms as diverse as prodrug catalysis and immune activity induction. We show that selection gene drives can eradicate diverse forms of genetic resistance in vitro. Finally, we demonstrate that model-informed switch engagement effectively targets pre-existing resistance in mouse models of solid tumors. These results establish selection gene drives as a powerful framework for evolution-guided anticancer therapy.

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.

Mechanism of ERBB2 gene overexpression by the formation of super-enhancer with genomic structural abnormalities in lung adenocarcinoma without clinically actionable genetic alterations

BACKGROUND

In an extensive genomic analysis of lung adenocarcinomas (LUADs), driver mutations have been recognized as potential targets for molecular therapy. However, there remain cases where target genes are not identified. Super-enhancers and structural variants are frequently identified in several hundred loci per case. Despite this, most cancer research has approached the analysis of these data sets separately, without merging and comparing the data, and there are no examples of integrated analysis in LUAD.

METHODS

We performed an integrated analysis of super-enhancers and structural variants in a cohort of 174 LUAD cases that lacked clinically actionable genetic alterations. To achieve this, we conducted both WGS and H3K27Ac ChIP-seq analyses using samples with driver gene mutations and those without, allowing for a comprehensive investigation of the potential roles of super-enhancer in LUAD cases.

RESULTS

We demonstrate that most genes situated in these overlapped regions were associated with known and previously unknown driver genes and aberrant expression resulting from the formation of super-enhancers accompanied by genomic structural abnormalities. Hi-C and long-read sequencing data further corroborated this insight. When we employed CRISPR-Cas9 to induce structural abnormalities that mimicked cases with outlier ERBB2 gene expression, we observed an elevation in ERBB2 expression. These abnormalities are associated with a higher risk of recurrence after surgery, irrespective of the presence or absence of driver mutations.

CONCLUSIONS

Our findings suggest that aberrant gene expression linked to structural polymorphisms can significantly impact personalized cancer treatment by facilitating the identification of driver mutations and prognostic factors, contributing to a more comprehensive understanding of LUAD pathogenesis.

Changing smoking habits and the occurrence of lung cancer in Sweden-a population analysis

BACKGROUND

The objective is to estimate the importance of the decrease of smoking habits in Sweden for the occurrence of lung cancer.

METHODS

The change in smoking habits in the general population was retrieved from surveys and on taxation of sale of cigarettes. We used data from the Swedish Cancer Register on incidence of lung cancer between 1970 and 2021, stratified for sex, age and cell type, and compared the occurrence overtime in ages between 40 and 84 years.

RESULTS

The sale of cigarettes peaked in 1980 to 1800 cigarettes per person and decreased to 600 per person in 2021. The change in incidence rates of squamous cell cancer and other cell types varied over time, sex, and age in a pattern that partly seems to be explained by change in the prevalence of daily smokers. The incidence of adenocarcinoma was similar in men and women 1970-2021 and increased, e.g. for women and men 75-79 years of age from around 20 cases in early 1970s to around 120 cases per 100 000 person-years in the 2020s.

CONCLUSIONS

Our data indicate that the risk of lung cancer several years after smoking cessation is less favourable than previously studies have indicated. There is a similar increase in the incidence of adenocarcinoma in men and women which is hard to explain only with changing smoking habits. The change from non-filter to filter cigarettes in the 1960s-1970s may be a contributing factor.

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.

Phenotypic noise and plasticity in cancer evolution

Non-genetic alterations can produce changes in a cell's phenotype. In cancer, these phenomena can influence a cell's fitness by conferring access to heritable, beneficial phenotypes. Herein, we argue that current discussions of 'phenotypic plasticity' in cancer evolution ignore a salient feature of the original definition: namely, that it occurs in response to an environmental change. We suggest 'phenotypic noise' be used to distinguish non-genetic changes in phenotype that occur independently from the environment. We discuss the conceptual and methodological techniques used to identify these phenomena during cancer evolution. We propose that the distinction will guide efforts to define mechanisms of phenotype change, accelerate translational work to manipulate phenotypes through treatment, and, ultimately, improve patient outcomes.

Tackling Non-Small Cell Lung Cancer in Young Adults: From Risk Factors and Genetic Susceptibility to Lung Cancer Profile and Outcomes

Lung cancer has traditionally been associated with advanced age; however, its increasing incidence among young adults raises concerning questions regarding its etiology and unique considerations for this population. In contrast to the older population, the onset of lung cancer at younger age may be attributed to a complex interplay of incompletely understood individual susceptibility and prevalent environmental risk factors beyond tobacco smoke exposure, such as radon gas and air pollution, which are widespread globally. Consequently, this leads to distinct clinical and molecular profiles, requiring a tailored approach. Furthermore, a diagnosis of cancer represents a threatening event during the prime years of a young person's life, prompting concern about career development, social aspects, fertility aspirations, and physical independence. This poses significant additional challenges for health care professionals in a field that remains underexplored. This comprehensive review recognizes lung cancer in young adults as a distinct entity, exploring its clinical and molecular characteristics, diverse predisposing factors, and priorities in terms of quality of life, with the aim of providing practical support to oncologists and enhancing our understanding of this under-researched population.

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.

A war on many fronts: cross disciplinary approaches for novel cancer treatment strategies

Cancer is a disease characterized by uncontrolled cellular growth where cancer cells take advantage of surrounding cellular populations to obtain resources and promote invasion. Carcinomas are the most common type of cancer accounting for almost 90% of cancer cases. One of the major subtypes of carcinomas are adenocarcinomas, which originate from glandular cells that line certain internal organs. Cancers such as breast, prostate, lung, pancreas, colon, esophageal, kidney are often adenocarcinomas. Current treatment strategies include surgery, chemotherapy, radiation, targeted therapy, and more recently immunotherapy. However, patients with adenocarcinomas often develop resistance or recur after the first line of treatment. Understanding how networks of tumor cells interact with each other and the tumor microenvironment is crucial to avoid recurrence, resistance, and high-dose therapy toxicities. In this review, we explore how mathematical modeling tools from different disciplines can aid in the development of effective and personalized cancer treatment strategies. Here, we describe how concepts from the disciplines of ecology and evolution, economics, and control engineering have been applied to mathematically model cancer dynamics and enhance treatment strategies.

Genotype-to-phenotype mapping of somatic clonal mosaicism via single-cell co-capture of DNA mutations and mRNA transcripts

Somatic mosaicism is a hallmark of malignancy that is also pervasively observed in human physiological aging, with clonal expansions of cells harboring mutations in recurrently mutated driver genes. Bulk sequencing of tissue microdissection captures mutation frequencies, but cannot distinguish which mutations co-occur in the same clones to reconstruct clonal architectures, nor phenotypically profile clonal populations to delineate how driver mutations impact cellular behavior. To address these challenges, we developed single-cell Genotype-to-Phenotype sequencing (scG2P) for high-throughput, highly-multiplexed, single-cell joint capture of recurrently mutated genomic regions and mRNA phenotypic markers in cells or nuclei isolated from solid tissues. We applied scG2P to aged esophagus samples from five individuals with high alcohol and tobacco exposure and observed a clonal landscape dominated by a large number of clones with a single driver event, but only rare clones with two driver mutations. NOTCH1 mutants dominate the clonal landscape and are linked to stunted epithelial differentiation, while TP53 mutants and double-driver mutants promote clonal expansion through both differentiation biases and increased cell cycling. Thus, joint single-cell highly multiplexed capture of somatic mutations and mRNA transcripts enables high resolution reconstruction of clonal architecture and associated phenotypes in solid tissue somatic mosaicism.

Molecular Heterogeneity in Leiomyosarcoma and Implications for Personalised Medicine

OPINION STATEMENT

Leiomyosarcoma (LMS) is one of the more common subtypes of soft tissue sarcomas (STS), accounting for about 20% of cases. Differences in anatomical location, risk of recurrence and histomorphological variants contribute to the substantial clinical heterogeneity in survival outcomes and therapy responses observed in patients. There is therefore a need to move away from the current one-size-fits-all treatment approach towards a personalised strategy tailored for individual patients. Over the past decade, tissue profiling studies have revealed key genomic features and an additional layer of molecular heterogeneity among patients, with potential utility for optimal risk stratification and biomarker-matched therapies. Furthermore, recent studies investigating intratumour heterogeneity and tumour evolution patterns in LMS suggest some key features that may need to be taken into consideration when designing treatment strategies and clinical trials. Moving forward, national and international collaborative efforts to aggregate expertise, data, resources and tools are needed to achieve a step change in improving patient survival outcomes in this disease of unmet need.

Decoding the interplay between genetic and non-genetic drivers of metastasis

Metastasis is a multistep process by which cancer cells break away from their original location and spread to distant organs, and is responsible for the vast majority of cancer-related deaths. Preventing early metastatic dissemination would revolutionize the ability to fight cancer. Unfortunately, the relatively poor understanding of the molecular underpinnings of metastasis has hampered the development of effective anti-metastatic drugs. Although it is now accepted that disseminating tumour cells need to acquire multiple competencies to face the many obstacles they encounter before reaching their metastatic site(s), whether these competencies are acquired through an accumulation of metastasis-specific genetic alterations and/or non-genetic events is often debated. Here we review a growing body of literature highlighting the importance of both genetic and non-genetic reprogramming events during the metastatic cascade, and discuss how genetic and non-genetic processes act in concert to confer metastatic competencies. We also describe how recent technological advances, and in particular the advent of single-cell multi-omics and barcoding approaches, will help to better elucidate the cross-talk between genetic and non-genetic mechanisms of metastasis and ultimately inform innovative paths for the early detection and interception of this lethal process.

Punctuational evolution is pervasive in distal site metastatic colonization

The evolution of metastasis represents a lethal stage of cancer progression. Yet, the evolutionary kinetics of metastatic disease remain unresolved. Here, using single cell CRISPR-Cas9 lineage tracing data, we show that in metastatic disease, gradual molecular evolution is punctuated by episodes of rapid evolutionary change associated with lineage divergence. By measuring punctuational effects across the metastatic cascade, we show that punctuational effects contribute more to the molecular diversity at distal site metastases compared to the paired primary tumor, suggesting qualitatively different modes of evolution may drive primary and metastatic tumor progression. This is the first empirical evidence for distinct patterns of molecular evolution at early and late stages of metastasis and demonstrates the complex interplay of cell intrinsic and extrinsic factors that shape lethal cancer.

The Function of the Immune System, Beyond Strategies Based on Cell-Autonomous Mechanisms, Determines Cancer Development: Immune Response and Cancer Development

Although cancer remains a challenging disease to treat, early detection and removal of primary tumors through surgery or chemotherapy/radiotherapy can offer hope for patients. The privilege paradigm in cancer biology suggests that cell-autonomous mechanisms play a central role in tumorigenesis. According to this paradigm, these cellular mechanisms are the primary focus for the prevention and treatment of cancers. However, this point of view does not present a comprehensive theory for the initiation of cancer and an effective therapeutic strategy. Having an incomplete understanding of the etiology of cancer, it is essential to re-examine previous assumptions about carcinogenesis and develop new, practical theories that can account for all available clinical and experimental evidence. This will not only help to gain a better understanding of the disease, but also offer new avenues for treatment. This review provides evidence suggesting a shift in focus from a cell-autonomous mechanism to systemic mechanisms, particularly the immune system, that are involved in cancer formation.

Targeting Senescent Alveolar Epithelial Cells Using Engineered Mesenchymal Stem Cell-Derived Extracellular Vesicles To Treat Pulmonary Fibrosis

Type 2 alveolar epithelial cell (AEC2) senescence is crucial to the pathogenesis of pulmonary fibrosis (PF). The nicotinamide adenine dinucleotide (NAD+)-consuming enzyme cluster of differentiation 38 (CD38) is a marker of senescent cells and is highly expressed in AEC2s of patients with PF, thus rendering it a potential treatment target. Umbilical cord mesenchymal stem cell (MSC)-derived extracellular vesicles (MSC-EVs) have emerged as a cell-free treatment with clinical application prospects in antiaging and antifibrosis treatments. Herein, we constructed CD38 antigen receptor membrane-modified MSC-EVs (CD38-ARM-MSC-EVs) by transfecting MSCs with a lentivirus loaded with a CD38 antigen receptor-CD8 transmembrane fragment fusion plasmid to target AEC2s and alleviate PF. Compared with MSC-EVs, the CD38-ARM-MSC-EVs engineered in this study showed a higher expression of the CD38 antigen receptor and antifibrotic miRNAs and targeted senescent AEC2s cells highly expressing CD38 in vitro and in naturally aged mouse models after intraperitoneal administration. CD38-ARM-MSC-EVs effectively restored the NAD+ levels, reversed the epithelial-mesenchymal transition phenotype, and rejuvenated senescent A549 cells in vitro, thereby mitigating multiple age-associated phenotypes and alleviating PF in aged mice. Thus, this study provides a technology to engineer MSC-EVs and support our CD38-ARM-MSC-EVs to be developed as promising agents with high clinical potential against PF.

Whole-genome doubling is a double-edged sword: the heterogeneous role of whole-genome doubling in various cancer types

Whole-genome doubling (WGD), characterized by the duplication of an entire set of chromosomes, is commonly observed in various tumors, occurring in approximately 30-40% of patients with different cancer types. The effect of WGD on tumorigenesis varies depending on the context, either promoting or suppressing tumor progression. Recent advances in genomic technologies and large-scale clinical investigations have led to the identification of the complex patterns of genomic alterations underlying WGD and their functional consequences on tumorigenesis progression and prognosis. Our comprehensive review aims to summarize the causes and effects of WGD on tumorigenesis, highlighting its dualistic influence on cancer cells. We then introduce recent findings on WGD-associated molecular signatures and genetic aberrations and a novel subtype related to WGD. Finally, we discuss the clinical implications of WGD in cancer subtype classification and future therapeutic interventions. Overall, a comprehensive understanding of WGD in cancer biology is crucial to unraveling its complex role in tumorigenesis and identifying novel therapeutic strategies. [BMB Reports 2024; 57(3): 125-134].

Clinical application of the Lung Cancer Compact PanelTM using various types of cytological specimens in patients with lung cancer

BACKGROUND

The Lung Cancer Compact PanelTM (compact panel) is a gene panel that can detect driver alterations with high sensitivity in liquid samples, including tumor cells. This study examined the ability of a compact panel to detect genetic mutations in liquid specimens used in clinical practice.

METHODS

Three cohorts, bronchoscopic biopsy forceps washing (washing cohort), pleural effusion (pleural cohort), and spinal fluid (spinal cohort), were analyzed using the compact panel. Liquid samples were added into the GM (Genemetrics) tubes and analyzed. The washing cohort assessed the concordance rate of gene panel analysis outcomes in tissue specimens derived from the primary tumor. Meanwhile, the pleural cohort investigated the impact of storing specimens for 8 weeks and more on nucleic acid and mutation detection rates.

RESULTS

In the washing cohort (n = 79), the concordance rate with mutations detected in tissues was 75/79 (94.9 %). This rate reached 100 % when focusing solely on driver alterations for treatment. The pleural cohort (n = 8) showed no deterioration in nucleic acid quality or quantity after 8 weeks of storage in GM tubes. Similarly, in the spinal cohort (n = 9), spinal fluid with malignant cells exhibited driver alterations similar to those in the primary tumor. These findings underscore the efficacy of the compact panel in accurately identifying genetic mutations in different liquid specimens.

CONCLUSIONS

The compact panel is a reliable tool for detecting driver alterations in various cytological specimens. Its consistent performance across diverse sample types emphasizes its potential for guiding targeted therapies for patients with lung cancer and enhancing precision medicine approaches.

Immunotherapy rechallenge of advanced lung adenocarcinoma with cadonilimab (PD-1/CTLA-4 Bi-specific antibody): a case report

Lung adenocarcinoma (ADC) is a common pulmonary malignant disease with poor prognosis. Immunotherapeutic strategies are the current cornerstone of first-line therapy in driver-negative advanced lung ADC, but there is no treatment standard once the disease has progressed after the first-line application of immune checkpoint inhibitors (ICIs). Clinically, immunotherapy rechallenges are being attempted. However, it is undeniable that there are still great limitations to rechallenging patients with single- or double-ICI immunotherapy though immunotherapy rechallenges can bring new benefits. Cadonilimab (AK104), a unique bi-specific antibody targeting PD-1/CTLA-4, has similar biological activity but lower toxicity than the combination of CTLA-4 and PD-1 antibodies. Herein, we report a case of advanced lung ADC rechallenged with cadonilimab as a posterior-line therapy. The condition of the patient was maintained at stable disease for 6 months. This might provide a new idea and choice for the challenge of immunotherapy resistance.

The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma

The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and high intratumoral heterogeneity present challenges to pathologists, prompting the development of artificial intelligence (AI) methods. Here we developed ANORAK (pyrAmid pooliNg crOss stReam Attention networK), encoding multiresolution inputs with an attention mechanism, to delineate growth patterns from hematoxylin and eosin-stained slides. In 1,372 lung adenocarcinomas across four independent cohorts, AI-based grading was prognostic of disease-free survival, and further assisted pathologists by consistently improving prognostication in stage I tumors. Tumors with discrepant patterns between AI and pathologists had notably higher intratumoral heterogeneity. Furthermore, ANORAK facilitates the morphological and spatial assessment of the acinar pattern, capturing acinus variations with pattern transition. Collectively, our AI method enabled the precision quantification and morphology investigation of growth patterns, reflecting intratumoral histological transitions in lung adenocarcinoma.

Liquid biopsy in lung cancer

Lung cancer is a highly prevalent malignancy worldwide and the primary cause of mortality. The absence of systematic and standardized diagnostic approaches for identifying potential pulmonary nodules, early-stage cancers, and indeterminate tumors has led clinicians to consider tissue biopsy and pathological sections as the preferred method for clinical diagnosis, often regarded as the gold standard. The conventional tissue biopsy is an invasive procedure that does not adequately capture the diverse characteristics and evolving nature of tumors. Recently, the concept of 'liquid biopsy' has gained considerable attention as a promising solution. Liquid biopsy is a non-invasive approach that facilitates repeated analysis, enabling real-time monitoring of tumor recurrence, metastasis, and response to treatment. Currently, liquid biopsy includes circulating tumor cells, circulating cell-free DNA, circulating tumor DNA, circulating cell-free RNA, extracellular vesicles, and other proteins and metabolites. With rapid progress in molecular technology, liquid biopsy has emerged as a highly promising and intriguing approach, yielding compelling results. This article critically examines the significant role and potential clinical implications of liquid biopsy in the diagnosis, treatment, and prognosis of lung cancer.

Using molecular characteristics to distinguish multiple primary lung cancers and intrapulmonary metastases

Objectives

Multiple lung cancers may present as multiple primary lung cancers (MPLC) or intrapulmonary metastasis (IPM) with variations in clinical stage, treatment, and prognosis. However, the existing differentiation criteria based on histology do not fully meet the clinical needs. Next-generation sequencing (NGS) may play an important role in assisting the identification of different pathologies. Here, we extended the relevant data by combining histology and NGS to develop detailed identification criteria for MPLC and IPM.

Materials and Methods

Patients with lung cancer (each patient had ≥2 tumors) were enrolled in the training (n = 22) and validation (n = 13) cohorts. Genomic profiles obtained from 450-gene-targeted NGS were analyzed, and the new criteria were developed based on our findings and pre-existing Martini & Melamed criteria and molecular benchmarks.

Results

The analysis of the training cohort indicated that patients identified with MPLC had no (or <2) trunk or shared mutations. However, 98.02% of mutations were branch mutations, and 69.23% of MPLC had no common mutations. In contrast, a higher percentage of trunk (33.08%) or shared (9.02%) mutations were identified in IPM, suggesting significant differences among mutated components. Subsequently, eight MPLC and five IPM cases were identified in the validation cohort, aligning with the independent imaging and pathologic distinction. Overall, the percentage of trunk and shared mutations was higher in patients with IPM than in patients with MPLC. Based on these results and the establishment of new determination criteria for MPLC and IPM, we emphasize that the type and number of shared variants based on histologic consistency assist in identification.

Conclusion

Determining genetic alterations may be an effective method for differentiating MPLC and IPM, and NGS can be used as a valuable assisting tool.

Leveraging Tissue-Specific Enhancer-Target Gene Regulatory Networks Identifies Enhancer Somatic Mutations That Functionally Impact Lung Cancer

Enhancers are noncoding regulatory DNA regions that modulate the transcription of target genes, often over large distances along with the genomic sequence. Enhancer alterations have been associated with various pathological conditions, including cancer. However, the identification and characterization of somatic mutations in noncoding regulatory regions with a functional effect on tumorigenesis and prognosis remain a major challenge. Here, we present a strategy for detecting and characterizing enhancer mutations in a genome-wide analysis of patient cohorts, across three lung cancer subtypes. Lung tissue-specific enhancers were defined by integrating experimental data and public epigenomic profiles, and the genome-wide enhancer-target gene regulatory network of lung cells was constructed by integrating chromatin three-dimensional architecture data. Lung cancers possessed a similar mutation burden at tissue-specific enhancers and exons but with differences in their mutation signatures. Functionally relevant alterations were prioritized on the basis of the pathway-level integration of the effect of a mutation and the frequency of mutations on individual enhancers. The genes enriched for mutated enhancers converged on the regulation of key biological processes and pathways relevant to tumor biology. Recurrent mutations in individual enhancers also affected the expression of target genes, with potential relevance for patient prognosis. Together, these findings show that noncoding regulatory mutations have a potential relevance for cancer pathogenesis and can be exploited for patient classification.

SIGNIFICANCE

Mapping enhancer-target gene regulatory interactions and analyzing enhancer mutations at the level of their target genes and pathways reveal convergence of recurrent enhancer mutations on biological processes involved in tumorigenesis and prognosis.

Measured Steps: Navigating the Path of Oligoprogressive Lung Cancer with Targeted and Immunotherapies

PURPOSE OF REVIEW

This review discusses the definitions, treatment modalities, management, future directions, and ongoing clinical trials of oligoprogressive disease in oncogene-driven and non-oncogene-driven NSCLC.

RECENT FINDINGS

During the last decades, diagnostic and treatment modalities for oligometastatic NSCLC have advanced significantly, leading to improved survival. Additionally, our understanding of the tumor biology of oligoprogressive disease has expanded. However, despite the efforts of organizations, such as EORTC, ESTRO, and ASTRO proposing definitions for oligometastatic and oligoprogressive disease, heterogeneity in definitions persists in (ongoing) trials. Recognizing the significance of subclassification within oligoprogressive disease in NSCLC and the varying risks associated with subsequent metastatic spread, there is a call for tailored management strategies. A consensus on standardized criteria for the definition of oligoprogressive disease is urgently needed and will not only facilitate meaningful comparisons between studies but also pave the way for the development of personalized treatment plans that take into account the heterogeneous nature of oligoprogressive disease.

CONIPHER: a computational framework for scalable phylogenetic reconstruction with error correction

Intratumor heterogeneity provides the fuel for the evolution and selection of subclonal tumor cell populations. However, accurate inference of tumor subclonal architecture and reconstruction of tumor evolutionary histories from bulk DNA sequencing data remains challenging. Frequently, sequencing and alignment artifacts are not fully filtered out from cancer somatic mutations, and errors in the identification of copy number alterations or complex evolutionary events (e.g., mutation losses) affect the estimated cellular prevalence of mutations. Together, such errors propagate into the analysis of mutation clustering and phylogenetic reconstruction. In this Protocol, we present a new computational framework, CONIPHER (COrrecting Noise In PHylogenetic Evaluation and Reconstruction), that accurately infers subclonal structure and phylogenetic relationships from multisample tumor sequencing, accounting for both copy number alterations and mutation errors. CONIPHER has been used to reconstruct subclonal architecture and tumor phylogeny from multisample tumors with high-depth whole-exome sequencing from the TRACERx421 dataset, as well as matched primary-metastatic cases. CONIPHER outperforms similar methods on simulated datasets, and in particular scales to a large number of tumor samples and clones, while completing in under 1.5 h on average. CONIPHER enables automated phylogenetic analysis that can be effectively applied to large sequencing datasets generated with different technologies. CONIPHER can be run with a basic knowledge of bioinformatics and R and bash scripting languages.

Defects in DNA damage responses in SWI/SNF mutant cells and their impact on immune responses

The mammalian SWI/SNF chromatin remodelling complexes are commonly dysregulated in cancer. These complexes contribute to maintaining genome stability through a variety of pathways. Recent research has highlighted an important interplay between genome instability and immune signalling, and evidence suggests that this interplay can modulate the response to immunotherapy. Here, we review emerging studies where direct evidence of this relationship has been uncovered in SWI/SNF deficient cells. We also highlight genome maintenance activities of SWI/SNF that could potentially shape immune responses and discuss potential therapeutic implications.

Computational immunogenomic approaches to predict response to cancer immunotherapies

Cancer immunogenomics is an emerging field that bridges genomics and immunology. The establishment of large-scale genomic collaborative efforts along with the development of new single-cell transcriptomic techniques and multi-omics approaches have enabled characterization of the mutational and transcriptional profiles of many cancer types and helped to identify clinically actionable alterations as well as predictive and prognostic biomarkers. Researchers have developed computational approaches and machine learning algorithms to accurately obtain clinically useful information from genomic and transcriptomic sequencing data from bulk tissue or single cells and explore tumours and their microenvironment. The rapid growth in sequencing and computational approaches has resulted in the unmet need to understand their true potential and limitations in enabling improvements in the management of patients with cancer who are receiving immunotherapies. In this Review, we describe the computational approaches currently available to analyse bulk tissue and single-cell sequencing data from cancer, stromal and immune cells, as well as how best to select the most appropriate tool to address various clinical questions and, ultimately, improve patient outcomes.

The role of APOBEC3B in lung tumor evolution and targeted cancer therapy resistance

In this study, the impact of the apolipoprotein B mRNA-editing catalytic subunit-like (APOBEC) enzyme APOBEC3B (A3B) on epidermal growth factor receptor (EGFR)-driven lung cancer was assessed. A3B expression in EGFR mutant (EGFRmut) non-small-cell lung cancer (NSCLC) mouse models constrained tumorigenesis, while A3B expression in tumors treated with EGFR-targeted cancer therapy was associated with treatment resistance. Analyses of human NSCLC models treated with EGFR-targeted therapy showed upregulation of A3B and revealed therapy-induced activation of nuclear factor kappa B (NF-κB) as an inducer of A3B expression. Significantly reduced viability was observed with A3B deficiency, and A3B was required for the enrichment of APOBEC mutation signatures, in targeted therapy-treated human NSCLC preclinical models. Upregulation of A3B was confirmed in patients with NSCLC treated with EGFR-targeted therapy. This study uncovers the multifaceted roles of A3B in NSCLC and identifies A3B as a potential target for more durable responses to targeted cancer therapy.

Imaging the master regulator of the antioxidant response in non-small cell lung cancer with positron emission tomography

Mutations in the NRF2-KEAP1 pathway are common in non-small cell lung cancer (NSCLC) and confer broad-spectrum therapeutic resistance, leading to poor outcomes. The cystine/glutamate antiporter, system xc-, is one of the >200 cytoprotective proteins controlled by NRF2, which can be non-invasively imaged by (S)-4-(3-18F-fluoropropyl)-l-glutamate ([18F]FSPG) positron emission tomography (PET). Through genetic and pharmacologic manipulation, we show that [18F]FSPG provides a sensitive and specific marker of NRF2 activation in advanced preclinical models of NSCLC. We validate imaging readouts with metabolomic measurements of system xc- activity and their coupling to intracellular glutathione concentration. A redox gene signature was measured in patients from the TRACERx 421 cohort, suggesting an opportunity for patient stratification prior to imaging. Furthermore, we reveal that system xc- is a metabolic vulnerability that can be therapeutically targeted for sustained tumour growth suppression in aggressive NSCLC. Our results establish [18F]FSPG as predictive marker of therapy resistance in NSCLC and provide the basis for the clinical evaluation of both imaging and therapeutic agents that target this important antioxidant pathway.

Whole-genome doubling in tissues and tumors

The overwhelming majority of proliferating somatic human cells are diploid, and this genomic state is typically maintained across successive cell divisions. However, failures in cell division can induce a whole-genome doubling (WGD) event, in which diploid cells transition to a tetraploid state. While some WGDs are developmentally programmed to produce nonproliferative tetraploid cells with specific cellular functions, unscheduled WGDs can be catastrophic: erroneously arising tetraploid cells are ill-equipped to cope with their doubled cellular and chromosomal content and quickly become genomically unstable and tumorigenic. Deciphering the genetics that underlie the genesis, physiology, and evolution of whole-genome doubled (WGD+) cells may therefore reveal therapeutic avenues to selectively eliminate pathological WGD+ cells.