APOBEC mutagenesis, kataegis, chromothripsis in EGFR-mutant osimertinib-resistant lung adenocarcinomas

APOBEC3 mutagenesis drives therapy resistance in breast cancer

Acquired genetic alterations drive resistance to endocrine and targeted therapies in metastatic breast cancer; however, the underlying processes engendering these alterations are largely uncharacterized. To identify the underlying mutational processes, we utilized a clinically annotated cohort of 3,880 patient samples with tumor-normal sequencing. Mutational signatures associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) enzymes were prevalent and enriched in post-treatment hormone receptor-positive cancers. These signatures correlated with shorter progression-free survival on antiestrogen plus CDK4/6 inhibitor therapy in hormone receptor-positive metastatic breast cancer. Whole-genome sequencing of breast cancer models and paired primary-metastatic samples demonstrated that active APOBEC3 mutagenesis promoted therapy resistance through characteristic alterations such as RB1 loss. Evidence of APOBEC3 activity in pretreatment samples illustrated its pervasive role in breast cancer evolution. These studies reveal APOBEC3 mutagenesis to be a frequent mediator of therapy resistance in breast cancer and highlight its potential as a biomarker and target for overcoming resistance.

APOBEC3 Activity Promotes the Survival and Evolution of Drug-Tolerant Persister Cells during EGFR Inhibitor Resistance in Lung Cancer

APOBEC mutagenesis is one of the most common endogenous sources of mutations in human cancer and is a major source of genetic intratumor heterogeneity. High levels of APOBEC mutagenesis are associated with poor prognosis and aggressive disease across diverse cancers, but the mechanistic and functional impacts of APOBEC mutagenesis on tumor evolution and therapy resistance remain relatively unexplored. To address this, we investigated the contribution of APOBEC mutagenesis to acquired therapy resistance in a model of EGFR-mutant non-small cell lung cancer. We find that inhibition of EGFR in lung cancer cells leads to a rapid and pronounced induction of APOBEC3 expression and activity. Functionally, APOBEC expression promotes the survival of drug-tolerant persister cells (DTP) following EGFR inhibition. Constitutive expression of APOBEC3B alters the evolutionary trajectory of acquired resistance to the EGFR inhibitor gefitinib, making it more likely that resistance arises through de novo acquisition of the T790M gatekeeper mutation and squamous transdifferentiation during the DTP state. APOBEC3B expression is associated with increased expression of the squamous cell transcription factor ΔNp63 and squamous cell transdifferentiation in gefitinib-resistant cells. Knockout of p63 in gefitinib-resistant cells reduces the expression of the ΔNp63 target genes IL-1α/β and sensitizes these cells to the third-generation EGFR inhibitor osimertinib. These results suggest that APOBEC activity promotes acquired resistance by facilitating evolution and transdifferentiation in DTPs and that approaches to target ΔNp63 in gefitinib-resistant lung cancers may have therapeutic benefit.

SIGNIFICANCE

APOBEC mutagenesis is a common source of genetic heterogeneity in cancer, and APOBEC mutational signatures are enriched in metastatic and drug-resistant tumors. However, the mechanisms through which APOBEC3 enzymes promote tumor evolution remain unknown. In this study, we show that APOBEC3 activity contributes to the development of therapy-resistant cancer cells by promoting evolution of DTP cells. These findings offer insights into the role of APOBEC mutagenesis in cancer progression.

Activating Mutations in the MET Kinase Domain Co-Occur With Other Driver Oncogenes and Mediate Resistance to Targeted Therapy in NSCLC

INTRODUCTION

MET tyrosine kinase domain (TKD) mutations have recently been characterized as de novo oncogenic drivers in NSCLC. Nevertheless, whether activating MET TKD mutations can confer resistance to targeted therapy in non-MET, oncogene-driven NSCLCs remains unclear.

METHODS

To characterize the genomic features of tumors with MET TKD mutations in oncogene-driven NSCLC, we performed tumor genomic profiling on two different cohorts of patients with NSCLC. Preclinical models of the most frequently observed MET TKD mutations were generated to determine the effect on sensitivity to targeted therapy. Treatment strategies to overcome MET TKD mutation-mediated resistance were further explored.

RESULTS

Genomic profiling of more than 115,000 patients with NSCLC found that activating MET TKD mutations are prevalent in 0.15% of cases, and that about half of them co-occur with another oncogenic driver, with a differential pattern in co-occurring MET TKD mutations according to the oncogenic alteration. A review of eight cases with sequential genomic testing revealed that the MET TKD mutation was acquired after systemic therapy in 88% of cases, with a potential contribution of APOBEC mutagenesis underlying this process. In vitro, MET TKD mutation conferred resistance to targeted therapy in diverse oncogene-driven models, which could be overcome by combinatorial treatment against both the primary oncogene and the MET TKD mutation.

CONCLUSIONS

MET TKD mutation can act as an off-target resistance mechanism in diverse oncogene-driven NSCLC. Combination therapy with an effective MET-targeted therapy can potentially overcome MET TKD mutation-mediated resistance.

Osimertinib in the Treatment of Epidermal Growth Factor Receptor-Mutant Early and Locally Advanced Stages of Non-Small-Cell Lung Cancer: Current Evidence and Future Perspectives

The treatment of epidermal growth factor receptor (EGFR)-mutant non-small-cell lung cancer (NSCLC) patients was dramatically revolutionized by the introduction of EGFR tyrosine kinase inhibitors in clinical practice, both in advanced and locally advanced/early stages. The present work focuses on osimertinib use in locally advanced and early NSCLC stages. Phase 3 clinical trials have supported the use of osimertinib as the new standard of care, both in the adjuvant setting and in locally advanced disease. The ADAURA study reported an overall survival (OS) advantage for adjuvant osimertinib in completely resected stage II-IIIA EGFR-mutant tumors, while the LAURA study proved a statistically significant benefit in progression-free survival (PFS) and a delay of central nervous system metastasis development in EGFR-mutant patients treated with osimertinib maintenance after concurrent chemoradiotherapy for locally advanced disease. In the neoadjuvant setting, data on osimertinib's efficacy are conflicting; therefore, the Neo-ADAURA study is evaluating the efficacy and safety of neoadjuvant osimertinib alone or in combination with chemotherapy in patients with stage II-IIIB NSCLC and common EGFR mutations. We discuss several issues that need to be clarified, such as the efficacy of the drug on uncommon mutations, the long-term impact on survival, and the management of resistance mechanisms. Moreover, we report the studies that are trying to identify potential biomarkers of response, such as the circulating tumor DNA (ctDNA), with the aim of selecting patients who will benefit most from osimertinib.

Single-Cell RNA Sequencing in Unraveling Acquired Resistance to EGFR-TKIs in Non-Small Cell Lung Cancer: New Perspectives

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) have demonstrated remarkable efficacy in treating non-small cell lung cancer (NSCLC), but acquired resistance greatly reduces efficacy and poses a significant challenge to patients. While numerous studies have investigated the mechanisms underlying EGFR-TKI resistance, its complexity and diversity make the existing understanding still incomplete. Traditional approaches frequently struggle to adequately reveal the process of drug resistance development through mean value analysis at the overall cellular level. In recent years, the rapid development of single-cell RNA sequencing technology has introduced a transformative method for analyzing gene expression changes within tumor cells at a single-cell resolution. It not only deepens our understanding of the tumor microenvironment and cellular heterogeneity associated with EGFR-TKI resistance but also identifies potential biomarkers of resistance. In this review, we highlight the critical role of single-cell RNA sequencing in lung cancer research, with a particular focus on its application to exploring the mechanisms of EGFR-TKI-acquired resistance in NSCLC. We emphasize its potential for elucidating the complexity of drug resistance mechanism and its promise in informing more precise and personalized treatment strategies. Ultimately, this approach aims to advance NSCLC treatment toward a new era of precision medicine.

Characterization of the genomic landscape in liver oligometastatic NSCLC

OBJECTIVES

Emerging data have shown that local treatment could provide clinical benefit for non-small cell lung cancer (NSCLC) patients with oligometastasis. Liver metastases have the worst prognosis in advanced NSCLC, but the genomic characteristics of liver oligometastasis remain unclear. The aim of our study was to elucidate the molecular features of liver oligometastatic NSCLC.

METHODS

Paired liver metastatic tissue samples and peripheral blood from 32 liver oligometastatic NSCLC patients were concurrently collected for comprehensive genomic analysis using next-generation sequencing.

RESULTS

A total of 206 mutated genes in 32 patients were detected, with a median of 4 mutations per sample. The most frequent alterations (> 10%) in liver oligometastasis were TP53 (72%), EGFR (50%), RB1 (19%) and SMARCA4 (12%). The co-occurrence rate of TP53 and RB1 in our cohort was significantly higher than that in the TCGA-LUAD cohort. Age, APOBEC, homologous recombination deficiency (HRD) and deficient mismatch repair (dMMR) established the mutational signature of liver oligometastatic NSCLC. The median tumor mutation burden (TMB) was 4.8 mutations/Mb. A total of 78.12% patients harbored at least one potentially actionable molecular alteration that may guide further targeted therapy according to the OncoKB evidence.

CONCLUSIONS

Our study comprehensively delineated the genomic characteristics of liver oligometastatic NSCLC - such findings were helpful to better understand the distinct clinic-biological features of oligometastasis and optimize personalized treatment of this population.

Automated real-world data integration improves cancer outcome prediction

The digitization of health records and growing availability of tumour DNA sequencing provide an opportunity to study the determinants of cancer outcomes with unprecedented richness. Patient data are often stored in unstructured text and siloed datasets. Here we combine natural language processing annotations1,2 with structured medication, patient-reported demographic, tumour registry and tumour genomic data from 24,950 patients at Memorial Sloan Kettering Cancer Center to generate a clinicogenomic, harmonized oncologic real-world dataset (MSK-CHORD). MSK-CHORD includes data for non-small-cell lung (n = 7,809), breast (n = 5,368), colorectal (n = 5,543), prostate (n = 3,211) and pancreatic (n = 3,109) cancers and enables discovery of clinicogenomic relationships not apparent in smaller datasets. Leveraging MSK-CHORD to train machine learning models to predict overall survival, we find that models including features derived from natural language processing, such as sites of disease, outperform those based on genomic data or stage alone as tested by cross-validation and an external, multi-institution dataset. By annotating 705,241 radiology reports, MSK-CHORD also uncovers predictors of metastasis to specific organ sites, including a relationship between SETD2 mutation and lower metastatic potential in immunotherapy-treated lung adenocarcinoma corroborated in independent datasets. We demonstrate the feasibility of automated annotation from unstructured notes and its utility in predicting patient outcomes. The resulting data are provided as a public resource for real-world oncologic research.

APOBEC3 activity promotes the survival and evolution of drug-tolerant persister cells during acquired resistance to EGFR inhibitors in lung cancer

APOBEC mutagenesis is one of the most common endogenous sources of mutations in human cancer and is a major source of genetic intratumor heterogeneity. High levels of APOBEC mutagenesis are associated with poor prognosis and aggressive disease across diverse cancers, but the mechanistic and functional impacts of APOBEC mutagenesis on tumor evolution and therapy resistance remain relatively unexplored. To address this, we investigated the contribution of APOBEC mutagenesis to acquired therapy resistance in a model of EGFR-mutant non-small cell lung cancer. We find that inhibition of EGFR in lung cancer cells leads to a rapid and pronounced induction of APOBEC3 expression and activity. Functionally, APOBEC expression promotes the survival of drug-tolerant persister cells (DTPs) following EGFR inhibition. Constitutive expression of APOBEC3B alters the evolutionary trajectory of acquired resistance to the EGFR inhibitor gefitinib, making it more likely that resistance arises through de novo acquisition of the T790M gatekeeper mutation and squamous transdifferentiation during the DTP state. APOBEC3B expression is associated with increased expression of the squamous cell transcription factor ΔNp63 and squamous cell transdifferentiation in gefitinib-resistant cells. Knockout of p63 in gefitinib-resistant cells reduces the expression of the ΔNp63 target genes IL1α/β and sensitizes these cells to the third-generation EGFR inhibitor osimertinib. These results suggest that APOBEC activity promotes acquired resistance by facilitating evolution and transdifferentiation in DTPs, and suggest that approaches to target ΔNp63 in gefitinib-resistant lung cancers may have therapeutic benefit.

A Genomics-Driven Artificial Intelligence-Based Model Classifies Breast Invasive Lobular Carcinoma and Discovers CDH1 Inactivating Mechanisms

Artificial intelligence (AI) systems can improve cancer diagnosis, yet their development often relies on subjective histologic features as ground truth for training. Herein, we developed an AI model applied to histologic whole-slide images using CDH1 biallelic mutations, pathognomonic for invasive lobular carcinoma (ILC) in breast neoplasms, as ground truth. The model accurately predicted CDH1 biallelic mutations (accuracy = 0.95) and diagnosed ILC (accuracy = 0.96). A total of 74% of samples classified by the AI model as having CDH1 biallelic mutations but lacking these alterations displayed alternative CDH1 inactivating mechanisms, including a deleterious CDH1 fusion gene and noncoding CDH1 genetic alterations. Analysis of internal and external validation cohorts demonstrated 0.95 and 0.89 accuracy for ILC diagnosis, respectively. The latent features of the AI model correlated with human-explainable histopathologic features. Taken together, this study reports the construction of an AI algorithm trained using a genetic rather than histologic ground truth that can robustly classify ILCs and uncover CDH1 inactivating mechanisms, providing the basis for orthogonal ground truth utilization for development of diagnostic AI models applied to whole-slide image. Significance: Genetic alterations linked to strong genotypic-phenotypic correlations can be utilized to develop AI systems applied to pathology that facilitate cancer diagnosis and biologic discoveries.

Topography of mutational signatures in non-small cell lung cancer: emerging concepts, clinical applications, and limitations

The genome of a cell is continuously battered by a plethora of exogenous and endogenous processes that can lead to damaged DNA. Repair mechanisms correct this damage most of the time, but failure to do so leaves mutations. Mutations do not occur in random manner, but rather typically follow a more or less specific pattern due to known or imputed mutational processes. Mutational signature analysis is the process by which the predominant mutational process can be inferred for a cancer and can be used in several contexts to study both the genesis of cancer and its response to therapy. Recent pan-cancer genomic efforts such as "The Cancer Genome Atlas" have identified numerous mutational signatures that can be categorized into single base substitutions, doublet base substitutions, or small insertions/deletions. Understanding these mutational signatures as they occur in non-small lung cancer could improve efforts at prevention, predict treatment response to personalized treatments, and guide the development of therapies targeting tumor evolution. For non-small cell lung cancer, several mutational signatures have been identified that correlate with exposures such as tobacco smoking and radon and can also reflect endogenous processes such as aging, APOBEC activity, and loss of mismatch repair. Herein, we provide an overview of the current knowledge of mutational signatures in non-small lung cancer.

Tumor suppressor heterozygosity and homologous recombination deficiency mediate resistance to front-line therapy in breast cancer

The co-occurrence of germline and somatic oncogenic alterations is frequently observed in breast cancer, but their combined biologic and clinical significance has not been evaluated. To assess the role of germline-somatic interactions on outcomes in routine practice, we developed an integrated clinicogenomic pipeline to analyze the genomes of over 4,500 patients with breast cancer. We find that germline (g) BRCA2 -associated tumors are enriched for RB1 loss-of-function mutations and manifest poor outcomes on standard-of-care, front-line CDK4/6 inhibitor (CDK4/6i) combinations. Amongst these tumors, g BRCA2 -related homologous recombination deficiency (HRD) as well as baseline RB1 LOH status promote acquisition of RB1 loss-of- function mutations under the selective pressure of CDK4/6i, causing therapy resistance. These findings suggest an alternative therapeutic strategy using sequential targeting of HRD in g BRCA- associated breast cancers through PARP inhibitors prior to CDK4/6i therapy to intercept deleterious RB1 -loss trajectories and thus suppress the emergence of CDK4/6 inhibitor resistance. More broadly, our findings demonstrate how germline-somatic driven genomic configurations shape response to systemic therapy and can be exploited therapeutically as part of biomarker-directed clinical strategies.

Loss of the DNA Repair Gene RNase H2 Identifies a Unique Subset of DDR-Deficient Leiomyosarcomas

Targeting the DNA damage response (DDR) pathway is an emerging therapeutic approach for leiomyosarcoma (LMS), and loss of RNase H2, a DDR pathway member, is a potentially actionable alteration for DDR-targeted treatments. Therefore, we designed a protein- and genomic-based RNase H2 screening assay to determine its prevalence and prognostic significance. Using a selective RNase H2 antibody on a pan-tumor microarray (TMA), RNase H2 loss was more common in LMS (11.5%, 9/78) than across all tumors (3.8%, 32/843). In a separate LMS cohort, RNase H2 deficiency was confirmed in uterine LMS (U-LMS, 21%, 23/108) and soft-tissue LMS (ST-LMS; 30%, 39/102). In the TCGA database, RNASEH2B homozygous deletions (HomDels) were found in 6% (5/80) of LMS cases, with a higher proportion in U-LMS (15%; 4/27) compared with ST-LMS (2%; 1/53). Using the SNiPDx targeted-NGS sequencing assay to detect biallelic loss of function in select DDR-related genes, we found RNASEH2B HomDels in 54% (19/35) of U-LMS cases with RNase H2 loss by IHC, and 7% (3/43) HomDels in RNase H2 intact cases. No RNASEH2B HomDels were detected in ST-LMS. In U-LMS patient cohort (n = 109), no significant overall survival difference was seen in patients with RNase H2 loss versus intact, or RNASEH2B HomDel (n = 12) versus Non-HomDel (n = 37). The overall diagnostic accuracy, sensitivity, and specificity of RNase H2 IHC for detecting RNA-SEH2B HomDels in U-LMS was 76%, 93%, and 71%, respectively, and it is being developed for future predictive biomarker driven clinical trials targeting DDR in U-LMS.

Cancer mutational signatures identification in clinical assays using neural embedding-based representations

While mutational signatures provide a plethora of prognostic and therapeutic insights, their application in clinical-setting, targeted gene panels is extremely limited. We develop a mutational representation model (which learns and embeds specific mutation signature connections) that enables prediction of dominant signatures with only a few mutations. We predict the dominant signatures across more than 60,000 tumors with gene panels, delineating their landscape across different cancers. Dominant signature predictions in gene panels are of clinical importance. These included UV, tobacco, and apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC) signatures that are associated with better survival, independently from mutational burden. Further analyses reveal gene and mutation associations with signatures, such as SBS5 with TP53 and APOBEC with FGFR3S249C. In a clinical use case, APOBEC signature is a robust and specific predictor for resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). Our model provides an easy-to-use way to detect signatures in clinical setting assays with many possible clinical implications for an unprecedented number of cancer patients.

UNG-RPA interaction governs the choice between high-fidelity and mutagenic uracil repair

Mammalian Uracil DNA glycosylase (UNG) removes uracils and initiates high-fidelity base excision repair to maintain genomic stability. During B cell development, activation-induced cytidine deaminase (AID) creates uracils that UNG processes in an error-prone fashion to accomplish immunoglobulin (Ig) somatic hypermutation (SHM) or class switch recombination (CSR). The mechanism that governs high-fidelity versus mutagenic uracil repair is not understood. The B cell tropic gammaherpesvirus (GHV) encodes a functional homolog of UNG that can process AID induced genomic uracils. GHVUNG does not support hypermutation, suggesting intrinsic properties of UNG influence repair outcome. Noting the structural divergence between the UNGs, we define the RPA interacting motif as the determinant of mutation outcome. UNG or RPA mutants unable to interact with each other, only support high-fidelity repair. In B cells, transversions at the Ig variable region are abated while CSR is supported. Thus UNG-RPA governs the generation of mutations and has implications for locus specific mutagenesis in B cells and deamination associated mutational signatures in cancer.

APOBEC3 mutagenesis drives therapy resistance in breast cancer

Acquired genetic alterations commonly drive resistance to endocrine and targeted therapies in metastatic breast cancer 1-7 , however the underlying processes engendering these diverse alterations are largely uncharacterized. To identify the mutational processes operant in breast cancer and their impact on clinical outcomes, we utilized a well-annotated cohort of 3,880 patient samples with paired tumor-normal sequencing data. The mutational signatures associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) enzymes were highly prevalent and enriched in post-treatment compared to treatment-naïve hormone receptor-positive (HR+) cancers. APOBEC3 mutational signatures were independently associated with shorter progression-free survival on antiestrogen plus CDK4/6 inhibitor combination therapy in patients with HR+ metastatic breast cancer. Whole genome sequencing (WGS) of breast cancer models and selected paired primary-metastatic samples demonstrated that active APOBEC3 mutagenesis promoted resistance to both endocrine and targeted therapies through characteristic alterations such as RB1 loss-of-function mutations. Evidence of APOBEC3 activity in pre-treatment samples illustrated a pervasive role for this mutational process in breast cancer evolution. The study reveals APOBEC3 mutagenesis to be a frequent mediator of therapy resistance in breast cancer and highlights its potential as a biomarker and target for overcoming resistance.

Targeting APOBECs in cancer: It's about timing

APOBEC3 cytidine deaminases have emerged as key drivers of mutagenesis in a wide spectrum of tumor types and are now appreciated to play a causal role in driving tumor evolution and drug resistance. As efforts to develop APOBEC3 inhibitors progress, understanding the timing and consequences of APOBEC3-mediated mutagenesis in distinct clinical contexts will be critical for guiding the development of anti-cancer therapeutic strategies.

Genomic Landscape of Pulmonary Sarcomatoid Carcinoma

PURPOSE

Pulmonary sarcomatoid carcinoma (PSC) is a rare aggressive subtype of non-small cell lung cancer (NSCLC) with limited therapeutic strategies. We attempted to elucidate the evolutionary trajectories of PSC using multiregional and longitudinal tumor samples.

MATERIALS AND METHODS

A total of 31 patients were enrolled in this study and 11 longitudinal samples were available from them. Using whole exome sequencing data, we analyzed the mutational signatures in both carcinomatous and sarcomatous areas in primary tumors of the 31 patients and longitudinal samples obtained from 11 patients. Furthermore, digital droplet polymerase chain reaction (ddPCR), and programmed death-ligand 1 (PD-L1) immunohistochemistry using the Ventana SP263 assay were performed.

RESULTS

TP53 was identified as the most frequently altered gene in the primary (74%) and metastatic (73%) samples. MET exon 14 skipping mutations, confirmed by ddPCR, and TP53 mutations were mutually exclusive; whereas, MET exon 14 skipping mutations frequently co-occurred with MDM2 amplification. Metastatic tumors showed dissimilar genetic profiles from either primary component. During metastasis, the signatures of APOBEC decreased in metastatic lesions compared with that in primary lesions. PSC showed higher MET and KEAP1 mutations and stronger PD-L1 protein expression compared with that recorded in other NSCLCs.

CONCLUSION

Decreased APOBEC signatures and subclonal diversity were detected during malignant progression in PSC. Frequent MET mutations and strong PD-L1 expression distinguished PSC from other NSCLCs. The aggressiveness and therapeutic difficulties of PSC were possibly attributable to profound intratumoral and intertumoral genetic diversity. Next-generation sequencing could suggest the appropriate treatment strategy for PSC.

Post-therapy emergence of an NBN reversion mutation in a patient with pancreatic acinar cell carcinoma

Pancreatic acinar cell carcinoma (PACC) is a rare form of pancreatic cancer that commonly harbors targetable alterations, including activating fusions in the MAPK pathway and loss-of-function (LOF) alterations in DNA damage response/homologous recombination DNA repair-related genes. Here, we describe a patient with PACC harboring both somatic biallelic LOF of NBN and an activating NTRK1 fusion. Upon disease progression following 13 months of treatment with folinic acid, fluorouracil, irinotecan, and oxaliplatin (FOLFIRINOX), genomic analysis of a metastatic liver biopsy revealed the emergence of a novel reversion mutation restoring the reading frame of NBN. To our knowledge, genomic reversion of NBN has not been previously reported as a resistance mechanism in any tumor type. The patient was treated with, but did not respond to, targeted treatment with a selective NTRK inhibitor. This case highlights the complex but highly actionable genomic landscape of PACC and underlines the value of genomic profiling of rare tumor types such as PACC.

Genomic and epigenomic basis of breast invasive lobular carcinomas lacking CDH1 genetic alterations

CDH1 (E-cadherin) bi-allelic inactivation is the hallmark alteration of breast invasive lobular carcinoma (ILC), resulting in its discohesive phenotype. A subset of ILCs, however, lack CDH1 genetic/epigenetic inactivation, and their genetic underpinning is unknown. Through clinical targeted sequencing data reanalysis of 364 primary ILCs, we identified 25 ILCs lacking CDH1 bi-allelic genetic alterations. CDH1 promoter methylation was frequent (63%) in these cases. Targeted sequencing reanalysis revealed 3 ILCs harboring AXIN2 deleterious fusions (n = 2) or loss-of-function mutation (n = 1). Whole-genome sequencing of 3 cases lacking bi-allelic CDH1 genetic/epigenetic inactivation confirmed the AXIN2 mutation and no other cell-cell adhesion genetic alterations but revealed a new CTNND1 (p120) deleterious fusion. AXIN2 knock-out in MCF7 cells resulted in lobular-like features, including increased cellular migration and resistance to anoikis. Taken together, ILCs lacking CDH1 genetic/epigenetic alterations are driven by inactivating alterations in other cell adhesion genes (CTNND1 or AXIN2), endorsing a convergent phenotype in ILC.

Lineage-specific intolerance to oncogenic drivers restricts histological transformation

Lung adenocarcinoma (LUAD) and small cell lung cancer (SCLC) are thought to originate from different epithelial cell types in the lung. Intriguingly, LUAD can histologically transform into SCLC after treatment with targeted therapies. In this study, we designed models to follow the conversion of LUAD to SCLC and found that the barrier to histological transformation converges on tolerance to Myc, which we implicate as a lineage-specific driver of the pulmonary neuroendocrine cell. Histological transformations are frequently accompanied by activation of the Akt pathway. Manipulating this pathway permitted tolerance to Myc as an oncogenic driver, producing rare, stem-like cells that transcriptionally resemble the pulmonary basal lineage. These findings suggest that histological transformation may require the plasticity inherent to the basal stem cell, enabling tolerance to previously incompatible oncogenic driver programs.

Preclinical Modeling of Pathway-Targeted Therapy of Human Lung Cancer in the Mouse

Animal models, particularly genetically engineered mouse models (GEMMs), continue to have a transformative impact on our understanding of the initiation and progression of hematological malignancies and solid tumors. Furthermore, GEMMs have been employed in the design and optimization of potent anticancer therapies. Increasingly, drug responses are assessed in mouse models either prior, or in parallel, to the implementation of precision medical oncology, in which groups of patients with genetically stratified cancers are treated with drugs that target the relevant oncoprotein such that mechanisms of drug sensitivity or resistance may be identified. Subsequently, this has led to the design and preclinical testing of combination therapies designed to forestall the onset of drug resistance. Indeed, mouse models of human lung cancer represent a paradigm for how a wide variety of GEMMs, driven by a variety of oncogenic drivers, have been generated to study initiation, progression, and maintenance of this disease as well as response to drugs. These studies have now expanded beyond targeted therapy to include immunotherapy. We highlight key aspects of the relationship between mouse models and the evolution of therapeutic approaches, including oncogene-targeted therapies, immunotherapies, acquired drug resistance, and ways in which successful antitumor strategies improve on efficiently translating preclinical approaches into successful antitumor strategies in patients.

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.

KIT genetic alterations in breast cancer

AIMS

Activating somatic mutations or gene amplification of KIT result in constitutive activation of its receptor tyrosine kinase, which is targetable in various solid tumours. Here, we sought to investigate the presence of KIT genetic alterations in breast cancer (BC) and characterise the histological and genomic features of these tumours.

METHODS

A retrospective analysis of 5,575 BCs previously subjected to targeted sequencing using the FDA-authorised Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Targets (MSK-IMPACT) assay was performed to identify BCs with KIT alterations. A histological assessment of KIT-altered BCs was conducted, and their repertoire of genetic alterations was compared with that of BCs lacking KIT genetic alterations, matched for age, histological type, oestrogen receptor/HER2 status and sample type.

RESULTS

We identified 18 BCs (0.32%), including 9 primary and 9 metastatic BCs, with oncogenic/likely oncogenic genetic alterations affecting KIT, including activating somatic mutations (n=4) or gene amplification (n=14). All KIT-altered BCs were of high histological grade, although no distinctive histological features were observed. When compared with BCs lacking KIT genetic alterations, no distinctive genetic features were identified. In two metastatic KIT-altered BCs in which the matched primary BC had also been analysed by MSK-IMPACT, the KIT mutations were found to be restricted to the metastatic samples, suggesting that they were late events in the evolution of these cancers.

CONCLUSIONS

KIT genetic alterations are vanishingly rare in BC. KIT-altered BCs are of high grade but lack distinctive histological features. Genetic alterations in KIT might be late events in the evolution and/or progression of BC.

Genomic Profiling Reveals Germline Predisposition and Homologous Recombination Deficiency in Pancreatic Acinar Cell Carcinoma

PURPOSE

To determine the genetic predisposition underlying pancreatic acinar cell carcinoma (PACC) and characterize its genomic features.

METHODS

Both somatic and germline analyses were performed using an Food and Drug Administration-authorized matched tumor/normal sequencing assay on a clinical cohort of 28,780 patients with cancer, 49 of whom were diagnosed with PACC. For a subset of PACCs, whole-genome sequencing (WGS; n = 12) and RNA sequencing (n = 6) were performed.

RESULTS

Eighteen of 49 (36.7%) PACCs harbored germline pathogenic variants in homologous recombination (HR) and DNA damage response (DDR) genes, including BRCA1 (n = 1), BRCA2 (n = 12), PALB2 (n = 2), ATM (n = 2), and CHEK2 (n = 1). Thirty-one PACCs displayed pure, and 18 PACCs harbored mixed acinar cell histology. Fifteen of 31 (48%) pure PACCs harbored a germline pathogenic variant affecting HR-/DDR-related genes. BRCA2 germline pathogenic variants (11 of 31, 35%) were significantly more frequent in pure PACCs than in pancreatic adenocarcinoma (86 of 2,739, 3.1%; P < .001), high-grade serous ovarian carcinoma (67 of 1,318, 5.1%; P < .001), prostate cancer (116 of 3,401, 3.4%; P < .001), and breast cancer (79 of 3,196, 2.5%; P < .001). Genomic features of HR deficiency (HRD) were detected in 7 of 12 PACCs undergoing WGS, including 100% (n = 6) of PACCs with germline HR-related pathogenic mutations and 1 of 6 PACCs lacking known pathogenic alterations in HR-related genes. Exploratory analyses revealed that in PACCs, the repertoire of somatic driver genetic alterations and the load of neoantigens with high binding affinity varied according to the presence of germline pathogenic alterations affecting HR-/DDR-related genes and/or HRD.

CONCLUSION

In a large pan-cancer cohort, PACC was identified as the cancer type with the highest prevalence of both BRCA2 germline pathogenic variants and genomic features of HRD, suggesting that PACC should be considered as part of the spectrum of BRCA-related malignancies.

Clinical utility of genomic signatures for the management of early and metastatic triple-negative breast cancer

PURPOSE OF REVIEW

This comprehensive review aims to provide timely and relevant insights into the current therapeutic landscape for triple-negative breast cancer (TNBC) and the molecular features underlying this subtype. It emphasizes the need for more reliable biomarkers to refine prognostication and optimize therapy, considering the aggressive nature of TNBC and its limited targeted treatment options.

RECENT FINDINGS

The review explores the multidisciplinary management of early TNBC, which typically involves systemic chemotherapy, surgery, and radiotherapy. It highlights the emergence of immune checkpoint inhibitors (ICIs), poly(ADP-ribose) polymerase (PARP) inhibitors, and antibody-drug conjugates (ADCs) as promising therapeutic strategies for TNBC. Recent clinical trials investigating the use of ICIs in combination with chemotherapy and the approval of pembrolizumab and atezolizumab for PD-L1-positive metastatic TNBC are discussed. The efficacy of PARP inhibitors and ADCs in treating TNBC patients with specific genetic alterations is also highlighted.

SUMMARY

The findings discussed in this review have significant implications for clinical practice and research in TNBC. The identification of distinct molecular subtypes through gene expression profiling has enabled a better understanding of TNBC heterogeneity and its clinical implications. This knowledge has the potential to guide treatment decisions, as different subtypes display varying responses to neoadjuvant chemotherapy. Furthermore, the review emphasizes the importance of developing reliable genomic and transcriptomic signatures as biomarkers to refine patient prognostication and optimize therapy selection in TNBC. Integrating these signatures into clinical practice may lead to more personalized treatment approaches, improving outcomes for TNBC patients.

Molecular Characterization of Endometrial Carcinomas in Black and White Patients Reveals Disparate Drivers with Therapeutic Implications

Although the incidence of endometrial carcinoma (EC) is similar in Black and White women, racial disparities are stark, with the highest mortality rates observed among Black patients. Here, analysis of 1,882 prospectively sequenced ECs using a clinical FDA-authorized tumor-normal panel revealed a significantly higher prevalence of high-risk histologic and molecular EC subtypes in self-identified Black (n = 259) compared with White (n = 1,623) patients. Clinically actionable alterations, including high tumor mutational burden/microsatellite instability, which confer benefit from immunotherapy, were less frequent in ECs from Black than from White patients. Ultramutated POLE molecular subtype ECs associated with favorable outcomes were rare in Black patients. Results were confirmed by genetic ancestry analysis. CCNE1 gene amplification, which is associated with aggressive clinical behavior, was more prevalent in carcinosarcomas occurring in Black than in White patients. ECs from Black and White patients display important differences in their histologic types, molecular subtypes, driver genetic alterations, and therapeutic targets.

SIGNIFICANCE

Our comprehensive analysis of prospectively clinically sequenced ECs revealed significant differences in their histologic and molecular composition and in the presence of therapeutic targets in Black versus White patients. These findings emphasize the importance of incorporating diverse populations into molecular studies and clinical trials to address EC disparities. This article is featured in Selected Articles from This Issue, p. 2293.

Clinicopathologic and genomic features of lobular like invasive mammary carcinoma: is it a distinct entity?

This study describes "lobular-like invasive mammary carcinomas" (LLIMCas), a group of low- to intermediate-grade invasive mammary carcinomas with discohesive, diffusely infiltrative cells showing retained circumferential membranous immunoreactivity for both E-cadherin and p120. We analyzed the clinical-pathologic features of 166 LLIMCas compared to 104 classical invasive lobular carcinomas (ILCs) and 100 grade 1 and 2 invasive ductal carcinomas (IDCs). Tumor size and pT stage of LLIMCas were intermediate between IDCs and ILCs, and yet often underestimated on imaging and showed frequent positive margins on the first resection. Despite histomorphologic similarities to classical ILC, the discohesion in LLIMCa was independent of E-cadherin/p120 immunophenotypic alteration. An exploratory, hypothesis-generating analysis of the genomic features of 14 randomly selected LLIMCas and classical ILCs (7 from each category) was performed utilizing an FDA-authorized targeted capture sequencing assay (MSK-IMPACT). None of the seven LLIMCas harbored CDH1 loss-of-function mutations, and none of the CDH1 alterations detected in two of the LLIMCas was pathogenic. In contrast, all seven ILCs harbored CDH1 loss-of-function mutations coupled with the loss of heterozygosity of the CDH1 wild-type allele. Four of the six evaluable LLIMCas were positive for CDH1 promoter methylation, which may partially explain the single-cell infiltrative morphology seen in LLIMCa. Further studies are warranted to better define the molecular basis of the discohesive cellular morphology in LLIMCa. Until more data becomes available, identifying LLIMCas and distinguishing them from typical IDCs and ILCs would be justified. In patients with LLIMCas, preoperative MRI should be entertained to guide surgical management.

Pharmacogenomics: Driving Personalized Medicine

Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all "-omics" fields (e.g., proteomics, transcriptomics, metabolomics, and metagenomics). This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. Food and Drug Administration approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multicomponent biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues, providing insights into the current status and future direction of health care. SIGNIFICANCE STATEMENT: Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.

Disrupting of family with sequence similarity 105, member A (Fam105a) deteriorates pancreatic β-cell physiology and insulin secretion in INS-1 cells

The role of "Family with sequence similarity 105, member A" (FAM105A) in pancreatic β-cell function in relation to type 2 diabetes mellitus (T2D) is not fully understood. To address this issue, various molecular and functional experiments were conducted on primary human islets and INS-1 cells. RNA-seq expression analysis showed that FAM105A is highly expressed in human islets and its expression is reduced in diabetic islets compared to healthy islets. FAM105A expression correlated negatively with HbA1c levels and body mass index (BMI). Co-expression analysis showed a significant correlation between FAM105A with PDX1, GCK, GLUT1 and INSR, but not the INS gene. Silencing of Fam105a impaired insulin release, content, glucose uptake, and mitochondria ATP content but did not affect cell viability, reactive oxygen species (ROS) or apoptosis levels. Silencing of Fam105a was associated with reduced Pdx1 and Glut2 expression at mRNA and protein levels. RNA-seq analysis of dysregulated genes in Fam105a-silenced cells showed an overall downregulation of gene expression in β-cells and insulin secretion pathway. Disrupting Pdx1 did not affect Fam105a expression in INS-1 cells. Overall, the results suggest that FAM105A plays an important role in pancreatic β-cells biology and may be involved in the development of T2D.

Molecular Biomarkers of Disease Outcomes and Mechanisms of Acquired Resistance to First-Line Osimertinib in Advanced EGFR-Mutant Lung Cancers

INTRODUCTION

Preferred first-line treatment for patients with metastatic EGFR-mutant lung cancer is osimertinib, yet it is not known whether patient outcomes may be improved by identifying and intervening on molecular markers associated with therapeutic resistance.

METHODS

All patients with metastatic EGFR-mutant lung cancer treated with first-line osimertinib at the Memorial Sloan Kettering Cancer Center (n = 327) were identified. Available pretreatment and postprogression tumor samples underwent targeted gene panel sequencing and mutational signature analysis using SigMA algorithm. Progression-free survival (PFS) and overall survival were estimated using the Kaplan-Meier method.

RESULTS

Using multivariate analysis, baseline atypical EGFR (median PFS = 5.8 mo, p < 0.001) and concurrent TP53/RB1 alterations (median PFS = 10.5 mo, p = 0.015) were associated with shorter PFS on first-line osimertinib. Of 95 patients with postprogression biopsies, acquired resistance mechanisms were identified in 52% (off-target, n = 24; histologic transformation, n = 14; on-target, n = 12), with MET amplification (n = 9), small cell lung transformation (n = 7), and acquired EGFR amplification (n = 7), the most frequently identified mechanisms. Although there was no difference in postprogression survival on the basis of identified resistance (p = 0.07), patients with subsequent second-line therapy tailored to postprogression biopsy results had improved postprogression survival (hazard ratio = 0.09, p = 0.006). The paired postprogression tumors had higher tumor mutational burden (p = 0.008) and further dominant APOBEC mutational signatures (p = 0.07) compared with the pretreatment samples.

CONCLUSIONS

Patients with EGFR-mutant lung cancer treated with first-line osimertinib have improved survival with treatment adaptation on the basis of identified mechanisms of resistance at time of progression using tissue-based genomic analysis. Further survival gains may be achieved using risk-based treatment adaptation of pretreatment genomic alterations.

Neuroendocrine neoplasms of the lung and gastrointestinal system: convergent biology and a path to better therapies

Neuroendocrine neoplasms (NENs) can develop in almost any organ and span a spectrum from well-differentiated and indolent neuroendocrine tumours (NETs) to poorly differentiated and highly aggressive neuroendocrine carcinomas (NECs), including small-cell lung cancer (SCLC). These neoplasms are thought to primarily derive from neuroendocrine precursor cells located throughout the body and can also arise through neuroendocrine transdifferentiation of organ-specific epithelial cell types. Hence, NENs constitute a group of tumour types that share key genomic and phenotypic characteristics irrespective of their site of origin, albeit with some organ-specific differences. The establishment of representative preclinical models for several of these disease entities together with analyses of human tumour specimens has provided important insights into crucial aspects of their biology with therapeutic implications. In this Review, we provide a comprehensive overview of the current understanding of NENs of the gastrointestinal system and lung from clinical and biological perspectives. Research on NENs has typically been siloed by the tumour site of origin, and a cross-cutting view might enable advances in one area to accelerate research in others. Therefore, we aim to emphasize that a better understanding of the commonalities and differences of NENs arising in different organs might more effectively inform clinical research to define therapeutic targets and ultimately optimize patient care.

Katdetectr: an R/bioconductor package utilizing unsupervised changepoint analysis for robust kataegis detection

BACKGROUND

Kataegis refers to the occurrence of regional genomic hypermutation in cancer and is a phenomenon that has been observed in a wide range of malignancies. A kataegis locus constitutes a genomic region with a high mutation rate (i.e., a higher frequency of closely interspersed somatic variants than the overall mutational background). It has been shown that kataegis is of biological significance and possibly clinically relevant. Therefore, an accurate and robust workflow for kataegis detection is paramount.

FINDINGS

Here we present Katdetectr, an open-source R/Bioconductor-based package for the robust yet flexible and fast detection of kataegis loci in genomic data. In addition, Katdetectr houses functionalities to characterize and visualize kataegis and provides results in a standardized format useful for subsequent analysis. In brief, Katdetectr imports industry-standard formats (MAF, VCF, and VRanges), determines the intermutation distance of the genomic variants, and performs unsupervised changepoint analysis utilizing the Pruned Exact Linear Time search algorithm followed by kataegis calling according to user-defined parameters.We used synthetic data and an a priori labeled pan-cancer dataset of whole-genome sequenced malignancies for the performance evaluation of Katdetectr and 5 publicly available kataegis detection packages. Our performance evaluation shows that Katdetectr is robust regarding tumor mutational burden and shows the fastest mean computation time. Additionally, Katdetectr reveals the highest accuracy (0.99, 0.99) and normalized Matthews correlation coefficient (0.98, 0.92) of all evaluated tools for both datasets.

CONCLUSIONS

Katdetectr is a robust workflow for the detection, characterization, and visualization of kataegis and is available on Bioconductor: https://doi.org/doi:10.18129/B9.bioc.katdetectr.