Copy number signature analysis tool and its application in prostate cancer reveals distinct mutational processes and clinical outcomes

Evaluating topography of mutational signatures with SigProfilerTopography

The mutations found in a cancer genome are shaped by diverse processes, each displaying a characteristic mutational signature that may be influenced by the genome's architecture. While prior analyses have evaluated the effect of topographical genomic features on mutational signatures, there has been no computational tool that can comprehensively examine this interplay. Here, we present SigProfilerTopography, a Python package that allows evaluating the effect of chromatin organization, histone modifications, transcription factor binding, DNA replication, and DNA transcription on the activities of different mutational processes. SigProfilerTopography elucidates the unique topographical characteristics of mutational signatures, unveiling their underlying biological and molecular mechanisms.

Microbial Interactions Induce the Mutational Signature of Mismatch Repair Deficiency in Colorectal Cancer and Associated with EPPK1 Mutations

To better understand the impact of microbial interactions on the clonal evolution of colorectal cancer (CRC), we conducted high-resolution profiling of the gut microbiome of 101 treatment-naïve primary CRC patients using nanopore sequencing. We performed an integrated analysis of microbiome and tumor exome data to identify symbiotic microbes that interactively influence the mutational processes and the subsequent clonality of CRC. Our results suggested that Dialister pneumosintes and Fusobacterium animalis were both associated with somatic EPPK1 mutations and promote SBS6 (mismatch repair deficiency, dMMR) activity. Notably, we showed that the symbiotic architecture of Dialister pneumosintes and Fusobacterium animalis undergoes significant changes with the mutational status of EPPK1. In addition, we identified specific metabolic pathways involving key metabolites that potentially mediate microbial interactions in CRC. These findings provide new insights into the interplay between the gut microbiome and the mutation landscape of colorectal cancer, thereby informing the clonal evolution of CRC and new strategies for precision medicine.

Longitudinal Profiling of Circulating Tumor DNA Reveals the Evolutionary Dynamics of Metastatic Prostate Cancer during Serial Therapy

Treatment decisions in metastatic castration-resistant prostate cancer are mostly guided by clinical variables, but efforts to molecularly monitor the disease remain hampered by challenges in acquiring tumor tissue repeatedly. In this study, we simultaneously profiled the genome copy number and exome in longitudinal plasma circulating tumor DNA (ctDNA) acquired before, during, and upon progression to serial treatments with androgen signaling inhibitors and taxane chemotherapy from 60 patients with metastatic castration-resistant prostate cancer (2-10 samples per patient). The genomic data were used to delineate the clonal substructure and evolutionary dynamics of each patient, and an evolutionary dynamic index was developed to measure the longitudinal changes of the tumor subclones. Treatment with androgen signaling inhibitors resulted in greater subclonal selection and population structure changes than taxane treatment. The subclones that emerged in association with serial therapy resistance harbored recurrent aberrations in previously identified and new candidate genes, with particular enrichment in genes related to PI3K-AKT signaling. These findings indicate that the integration of detailed clinical and genomic data can provide a framework for future unbiased genomic applications for ctDNA in the clinic to enable precision medicine. Significance: Profiling of the genomic copy number changes and mutations in circulating tumor DNA collected longitudinally from prostate cancer patients receiving serial life-prolonging therapies elucidates evolutionary dynamics and identifies emerging resistant subclones.

Identification of CACNB1 protein as an actionable therapeutic target for hepatocellular carcinoma via metabolic dysfunction analysis in liver diseases: An integrated bioinformatics and machine learning approach for precise therapy

In addition to histological evaluation for nonalcoholic fatty liver disease (NAFLD), a comprehensive analysis of the metabolic landscape is urgently needed to categorize patients into distinct subgroups for precise treatment. In this study, a total of 806 NAFLD and 267 normal liver samples were comprehensively analyzed. Alterations in 114 metabolic pathways were investigated and two distinct metabolic clusters were identified. Single-cell RNA sequencing (scRNA-seq) analysis was utilized to decipher the metabolic activities within the microenvironment of NAFLD-derived liver cirrhosis. A refined fibrosis prediction model was developed using a Gaussian Mixture Model (GMM), demonstrating superior performance in fibrosis discrimination across multiple independent cohorts. Additionally, using The Cancer Genome Atlas (TCGA), CACNB1 protein was identified as a promising therapeutic target for hepatocellular carcinoma (HCC) patients with elevated metabolic dysfunction scores (MBDS). Machine learning algorithms were applied to MBDS-related genes to select an optimal prognostic model for HCC. All the models were trained in an HCC cohort obtained from the Gene Expression Omnibus (GEO), and the best model was validated in two independent HCC datasets: the TCGA-HCC cohort and LIRI-JP cohort. Overall, we provide insights of metabolic molecular subtyping and its potential clinical applicability in risk stratification for NAFLD and HCC individuals.

Detecting homologous recombination deficiency for breast cancer through integrative analysis of genomic data

Homologous recombination deficiency (HRD) leads to genomic instability, and patients with HRD can benefit from HRD-targeting therapies. Previous studies have primarily focused on identifying HRD biomarkers using data from a single technology. Here we integrated features from different genomic data types, including total copy number (CN), allele-specific copy number (ASCN) and single nucleotide variants (SNV). Using a semi-supervised method, we developed HRD classifiers from 1404 breast tumours across two datasets based on their BRCA1/2 status, demonstrating improved HRD identification when aggregating different data types. Notably, HRD-positive tumours in ER-negative disease showed improved survival post-adjuvant chemotherapy, while HRD status strongly correlated with neoadjuvant treatment response. Furthermore, our analysis of cell lines highlighted a sensitivity to PARP inhibitors, particularly rucaparib, among predicted HRD-positive lines. Exploring somatic mutations outside BRCA1/2, we confirmed variants in several genes associated with HRD. Our method for HRD classification can adapt to different data types or resolutions and can be used in various scenarios to help refine patient selection for HRD-targeting therapies that might lead to better clinical outcomes.

Predicting chemotherapy responsiveness in gastric cancer through machine learning analysis of genome, immune, and neutrophil signatures

BACKGROUND

Gastric cancer is a major oncological challenge, ranking highly among causes of cancer-related mortality worldwide. This study was initiated to address the variability in patient responses to combination chemotherapy, highlighting the need for personalized treatment strategies based on genomic data.

METHODS

We analyzed whole-genome and RNA sequences from biopsy specimens of 65 advanced gastric cancer patients before their chemotherapy treatment. Using machine learning techniques, we developed a model with 123 omics features, such as immune signatures and copy number variations, to predict their chemotherapy outcomes.

RESULTS

The model demonstrated a prediction accuracy of 70-80% in forecasting chemotherapy responses in both test and validation cohorts. Notably, tumor-associated neutrophils emerged as significant predictors of treatment efficacy. Further single-cell analyses from cancer tissues revealed different neutrophil subgroups with potential antitumor activities suggesting their usefulness as biomarkers for treatment decisions.

CONCLUSIONS

This study confirms the utility of machine learning in advancing personalized medicine for gastric cancer by identifying tumor-associated neutrophils and their subgroups as key indicators of chemotherapy response. These findings could lead to more tailored and effective treatment plans for patients.

Integration of multiple machine learning approaches develops a gene mutation-based classifier for accurate immunotherapy outcomes

In addition to traditional biomarkers like PD-(L)1 expression and tumor mutation burden (TMB), more reliable methods for predicting immune checkpoint blockade (ICB) response in cancer patients are urgently needed. This study utilized multiple machine learning approaches on nonsynonymous mutations to identify key mutations that are most significantly correlated to ICB response. We proposed a classifier, Gene mutation-based Predictive Signature (GPS), to categorize patients based on their predicted response and clinical outcomes post-ICB therapy. GPS outperformed conventional predictors when validated in independent cohorts. Multi-omics analysis and multiplex immunohistochemistry (mIHC) revealed insights into tumor immunogenicity, immune responses, and the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) across different GPS groups. Finally, we validated distinct responses of different GPS samples to ICB in an ex-vivo tumor organoid-PBMC co-culture model. Overall, our findings highlight a simple, robust classifier for accurate ICB response prediction, which could reduce costs, shorten testing times, and facilitate clinical implementation.

Functional genomics pipeline identifies CRL4 inhibition for the treatment of ovarian cancer

BACKGROUND

The goal of precision oncology is to find effective therapeutics for every patient. Through the inclusion of emerging therapeutics in a high-throughput drug screening platform, our functional genomics pipeline inverts the common paradigm to identify patient populations that are likely to benefit from novel therapeutic strategies.

APPROACH

Utilizing drug screening data across a panel of 46 cancer cell lines from 11 tumor lineages, we identified an ovarian cancer-specific sensitivity to the first-in-class CRL4 inhibitors KH-4-43 and 33-11. CRL4 (i.e., Cullin-4 RING E3 ubiquitin ligase) is known to be dysregulated in a variety of cancer contexts, making it an attractive therapeutic target. Unlike proteasome inhibitors that are associated with broad toxicity, CRL4 inhibition offers the potential for tumor-specific effects.

RESULTS

We observed that CRL4 inhibition negatively regulates core gene signatures that are upregulated in ovarian tumors and significantly slowed tumor growth as compared to the standard of care, cisplatin, in OVCAR8 xenografts. Building on this, we performed combination drug screening in conjunction with proteomic and transcriptomic profiling to identify ways to improve the antitumor effects of CRL4 inhibition in ovarian cancer models. CRL4 inhibition consistently resulted in activation of the mitogen-activated protein kinase (MAPK) signaling cascade at both the transcriptomic and protein levels, suggesting that survival signaling is induced in response to CRL4 inhibition. These observations were concordant with the results of the combination drug screens in seven ovarian cancer cell lines that showed CRL4 inhibition cooperates with MEK inhibition. Preclinical studies in OVCAR8 and A2780 xenografts confirmed the therapeutic potential of the combination of KH-4-43 and trametinib, which extended overall survival and slowed tumor progression relative to either single agent or the standard of care.

CONCLUSIONS

Together, these data demonstrate the prospective utility of functional modeling pipelines for therapeutic development and underscore the clinical potential of CRL4 inhibition in the ovarian cancer context.

HIGHLIGHTS

A precision medicine pipeline identifies ovarian cancer sensitivity to CRL4 inhibitors. CRL4 inhibition induces activation of MAPK signalling as identified by RNA sequencing, proteomics, and phosphoproteomics. Inhibitor combinations that target both CRL4 and this CRL4 inhibitor-induced survival signalling enhance ovarian cancer sensitivity to treatment.

Homologous recombination deficiency (HRD) diagnostics: underlying mechanisms and new perspectives

Homologous recombination deficiency (HRD) is considered a universal and effective sign of a tumor's sensitivity to poly(ADP-ribose) polymerase (PARP) inhibitors. HRD diagnostics have undergone several stages of transformations: from detection of point mutations in HR-related genes and large regions with loss of heterozygosity detected using single-nucleotide polymorphism arrays to whole-genome signatures of single-nucleotide variants, large genomic rearrangements (LGRs), and copy number alterations. All these methods have their own advantages and limitations. HRD tests, based on signatures of LGRs and copy number alterations, show in hindsight that some progenitor cells have possessed HRD status but not the current state of the genome. The aim of this review was to compare different methods of HRD detection and mechanisms of formation of HRD-specific LGRs. In the last several years, new data appeared implying a crucial role of proteins BRCA1 and BRCA2 in the resolution of stalled replication forks that may be associated with at least some of LGRs observed in HRD-positive tumors. Reviewing current knowledge on these mechanisms, distributions of different LGR types, and limitations of sequencing technologies and algorithms of data analysis, we offer some new perspectives on HRD diagnostics. We hope that this review will help to accelerate the development of new diagnostic approaches in this important field of molecular oncology.

Addition of SHR-1701 to first-line capecitabine and oxaliplatin (XELOX) plus bevacizumab for unresectable metastatic colorectal cancer

This phase 2/3 trial (NCT04856787) assessed the efficacy and safety of SHR-1701, a bifunctional protein targeting PD-L1 and TGF-β, in combination with BP102 (a bevacizumab biosimilar) and XELOX (capecitabine plus oxaliplatin) as a first-line treatment for unresectable metastatic colorectal cancer (mCRC). In this phase 2 study, a total of 62 patients with untreated, histologically confirmed colorectal adenocarcinoma and no prior systemic therapy for metastatic disease were enrolled. Patients received SHR-1701 (30 mg/kg), bevacizumab (7.5 mg/kg), and oxaliplatin (130 mg/m2) intravenously on day 1, along with oral capecitabine (1 g/m2 twice daily) on days 1-14 of 21-day cycles. Up to eight induction cycles were administered, followed by maintenance therapy for responders or those with stable disease. The primary endpoints were safety and objective response rate (ORR) per RECIST v1.1. The combination achieved an ORR of 59.7% and a disease control rate (DCR) of 83.9%. Median progression-free survival (PFS) was 10.3 months (95% CI: 8.3-13.7), with 6- and 12-month PFS rates of 77.2% and 41.3%, respectively. The estimated 12-month overall survival (OS) rate was 67.7%. Grade ≥3 treatment-related adverse events (TRAEs) were reported in 59.7% of patients, with anemia and neutropenia (8.1% each) being the most common. Retrospective DNA sequencing revealed that high tumor mutational burden, neo-antigens, and SBS15 enrichment correlated with better responses. Elevated baseline lactate dehydrogenase was linked to shorter PFS. SHR-1701 combined with XELOX and bevacizumab demonstrated a manageable safety profile and potent antitumor activity in unresectable mCRC.

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Proteogenomic analysis reveals non-small cell lung cancer subtypes predicting chromosome instability, and tumor microenvironment

Non-small cell lung cancer (NSCLC) is histologically classified into lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LSCC). However, some tumors are histologically ambiguous and other pathophysiological features or microenvironmental factors may be more prominent. Here we report integrative multiomics analyses using data for 229 patients from a Korean NSCLC cohort and 462 patients from previous multiomics studies. Histological examination reveals five molecular subtypes, one of which is a NSCLC subtype with PI3K-Akt pathway upregulation, showing a high proportion of metastasis and poor survival outcomes regardless of any specific NSCLC histology. Proliferative subtypes are present in LUAD and LSCC, which show strong associations with whole genome doubling (WGD) events. Comprehensive characterization of the immune microenvironment reveals various immune cell compositions and neoantigen loads across molecular subtypes, which predicting different prognoses. Immunological subtypes exhibit a hot tumor-enriched state and a higher efficacy of adjuvant therapy.

Unravelling mutational signatures with plasma circulating tumour DNA

The use of circulating tumour DNA (ctDNA) to profile mutational signatures represents a non-invasive opportunity for understanding cancer mutational processes. Here we present MisMatchFinder, a liquid biopsy approach for mutational signature detection using low-coverage whole-genome sequencing of ctDNA. Through analysis of 375 plasma samples across 9 cancers, we demonstrate that MisMatchFinder accurately infers single-base and doublet-base substitutions, as well as insertions and deletions to enhance the detection of ctDNA and clinically relevant mutational signatures.

A comprehensive comparison of tools for fitting mutational signatures

Mutational signatures connect characteristic mutational patterns in the genome with biological or chemical processes that take place in cancers. Analysis of mutational signatures can help elucidate tumor evolution, prognosis, and therapeutic strategies. Although tools for extracting mutational signatures de novo have been extensively benchmarked, a similar effort is lacking for tools that fit known mutational signatures to a given catalog of mutations. We fill this gap by comprehensively evaluating twelve signature fitting tools on synthetic mutational catalogs with empirically driven signature weights corresponding to eight cancer types. On average, SigProfilerSingleSample and SigProfilerAssignment/MuSiCal perform best for small and large numbers of mutations per sample, respectively. We further show that ad hoc constraining the list of reference signatures is likely to produce inferior results. Evaluation of real mutational catalogs suggests that the activity of signatures that are absent in the reference catalog poses considerable problems to all evaluated tools.

Genomic and transcriptomic profiling of inflammatory breast cancer reveals distinct molecular characteristics to non-inflammatory breast cancers

PURPOSE

Inflammatory breast cancer (IBC), a rare and highly aggressive form of breast cancer, accounts for 10% of breast cancer-related deaths. Previous omics studies of IBC have focused solely on one of genomics or transcriptomics and did not discover common differences that could distinguish IBC from non-IBC.

METHODS

Seventeen IBC patients and five non-IBC patients as well as additional thirty-three Asian breast cancer samples from TCGA-BRCA were included for the study. We performed whole-exon sequencing (WES) to investigate different somatic genomic alterations, copy number variants, and large structural variants between IBC and non-IBC. Bulk RNA sequencing (RNA-seq) was performed to examine the differentially expressed genes, pathway enrichment, and gene fusions. WES and RNA-seq data were further investigated in combination to discover genes that were dysregulated in both genomics and transcriptomics.

RESULTS

Copy number variation analysis identified 10 cytobands that showed higher frequency in IBC. Structural variation analysis showed more frequent deletions in IBC. Pathway enrichment and immune infiltration analysis indicated increased immune activation in IBC samples. Gene fusions including CTSC-RAB38 were found to be more common in IBC. We demonstrated more commonly dysregulated RAS pathway in IBC according to both WES and RNA-seq. Inhibitors targeting RAS signaling and its downstream pathways were predicted to possess promising effects in IBC treatment.

CONCLUSION

We discovered differences unique in Asian women that could potentially explain IBC etiology and presented RAS signaling pathway as a potential therapeutic target in IBC treatment.

Impaired neutrophil-mediated cell death drives Ewing's Sarcoma in the background of Down syndrome

Introduction

Ewing Sarcoma (EWS) has been reported in seven children with Down syndrome (DS). To date, a detailed assessment of this solid tumour in DS patients is yet to be made.

Methods

Here, we characterise a chemo-resistant mediastinal EWS in a 2-year-old DS child, the youngest ever reported case, by exploiting sequencing approaches.

Results

The tumour showed a neuroectodermal development driven by the EWSR1-FLI1 fusion. The inherited myeloperoxidase deficiency of the patient caused failure of neutrophil-mediated cell death and promoted genomic instability.

Discussion

In this context, the tumour underwent genome-wide near haploidisation resulting in a massive overexpression of pro-inflammatory cytokines. Recruitment of defective neutrophils fostered rapid evolution of this EWS.

Genomic alterations in the stepwise progression from normal mucosa to metastasizing oral squamous cell carcinoma

Introduction

The aim of this study was to investigate the genomic changes that occur in the development from dysplasia, cancer and to regional metastases in patients with oral cavity squamous cell carcinoma (OSCC).

Material and methods

We included OSCC patients with lymph node metastases at diagnosis, treated with primary surgery at Rigshospitalet, University of Copenhagen in the period 2007-2014. The resected tumor specimens were evaluated by a pathologist, who marked areas of morphologically normal tissue and dysplasia surrounding the cancer, two areas from the cancer tissue, and one area within the lymph node metastases. From these areas a punch biopsy was taken, and DNA from each sample was extracted and sequenced using Illumina's TSO500 HT cancer panel.

Results

From 51 OSCC patients, 255 samples were included, comprising a wide variety of genomic alterations. Substantial intratumor heterogeneity was found. The most commonly mutated gene was TP53, mutated in 65% of all samples. Only two patients had no TP53 mutation in any samples. We found that morphologically normal appearing mucosa as well as surrounding dysplasia also contained malignant mutations, supporting the theory of field cancerization. There was a significant lower average tumor mutational burden (TMB) in the lymph node metastases compared to the primary tumors, supporting the theory of clonal selection.

Conclusion

Substantial inter- and intratumor genomic heterogeneity was found. Mutation of TP53 was the most common and was present in all but two patients. Our data strongly supports the theory of clonal selection and the theory of field cancerization.

Proteogenomic characterization identifies clinical subgroups in EGFR and ALK wild-type never-smoker lung adenocarcinoma

Patients with lung adenocarcinoma who have never smoked (NSLA) and lack key driver mutations, such as those in the EGFR and ALK genes, face limited options for targeted therapies. They also tend to have poorer outcomes with immune checkpoint inhibitors than lung cancer patients who have a history of smoking. The proteogenomic profile of nonsmoking lung adenocarcinoma patients without these oncogenic driver mutations is poorly understood, which complicates the precise molecular classification of these cancers and highlights a significant area of unmet clinical need. This study analyzed the genome, transcriptome, and LC‒MS/MS-TMT-driven proteome data of tumors obtained from 99 Korean never-smoker lung adenocarcinoma patients. NSLA tumors without EGFR or ALK driver oncogenes were classified into four proteogenomic subgroups: proliferation, angiogenesis, immune, and metabolism subgroups. These 4 molecular subgroups were strongly associated with distinct clinical outcomes. The proliferation and angiogenesis subtypes were associated with a poorer prognosis, while the immune subtype was associated with the most favorable outcome, which was validated in an external lung cancer dataset. Genomic-wide impacts were analyzed, and significant correlations were found between copy number alterations and both the transcriptome and proteome for several genes, with enrichment in the ERBB, neurotrophin, insulin, and MAPK signaling pathways. Proteogenomic analyses suggested several targetable genes and proteins, including CDKs and ATR, as potential therapeutic targets in the proliferation subgroup. Upregulated cytokines, such as CCL5 and CXCL13, in the immune subgroup may serve as potential targets for combination immunotherapy. Our comprehensive proteogenomic analysis revealed the molecular subtypes of EGFR- and ALK-wild-type NSLA with significant unmet clinical needs.

The genomic landscape of lung cancer in never-smokers from the Women's Health Initiative

Over 200,000 individuals are diagnosed with lung cancer in the United States every year, with a growing proportion of cases, especially lung adenocarcinoma, occurring in individuals who have never smoked. Women over the age of 50 comprise the largest affected demographic. To understand the genomic drivers of lung adenocarcinoma and therapeutic response in this population, we performed whole genome and/or whole exome sequencing on 73 matched lung tumor/normal pairs from postmenopausal women who participated in the Women's Health Initiative. Somatic copy number alterations showed little variation by smoking status, suggesting that aneuploidy may be a general characteristic of lung cancer regardless of smoke exposure. Similarly, clock-like and APOBEC mutation signatures were prevalent but did not differ in tumors from smokers and never-smokers. However, mutations in both EGFR and KRAS showed unique allelic differences determined by smoking status that are known to alter tumor response to targeted therapy. Mutations in the MYC-network member MGA were more prevalent in tumors from smokers. Fusion events in ALK, RET, and ROS1 were absent, likely due to age-related differences in fusion prevalence. Our work underscores the profound effect of smoking status, age, and sex on the tumor mutational landscape and identifies areas of unmet medical need.

Identification of pathogenic germline variants in a large Chinese lung cancer cohort by clinical sequencing

Genetic factors play significant roles in the tumorigenicity of lung cancer; however, there is lack of systematic and large-scale characterization of pathogenic germline variants for lung cancer. In this study, germline variants in 146 preselected cancer-susceptibility genes were detected in 17 904 Chinese lung cancer patients by clinical next-generation sequencing. Among 17 904 patients, 1738 patients (9.7%) carried 1840 pathogenic/likely pathogenic (P/LP) variants from 87 cancer-susceptibility genes. SBDS (SBDS ribosome maturation factor) (1.37%), TSHR (thyroid stimulating hormone receptor) (1.20%), BLM (BLM RecQ like helicase) (0.62%), BRCA2 (BRCA2 DNA repair associated) (0.62%), and ATM (ATM serine/threonine kinase) (0.45%) were the top five genes with the highest overall prevalence. The top mutated pathways were all involved in DNA damage repair (DDR). Case-control analysis showed SBDS c.184A>T(p.K62*), TSHR c.1574T>C(p.F525S), BRIP1 (BRCA1 interacting helicase 1) c.1018C>T(p.L340F), and MUTYH (mutY DNA glycosylase) c.55C>T(p.R19*) were significantly associated with increased lung cancer risk (q value < 0.05). P/LP variants in certain genes were associated with early onset of lung cancer. Our study indicates that Chinese lung cancer patients have a higher prevalence of P/LP variants than previously reported. P/LP variants are distributed in multiple pathways and dominated by DNA damage repair-associated pathways. The association between identified P/LP variants and lung cancer risk requires further studies for verification.

Integrated analysis of purine metabolism assists in predicting prognosis and treatment decisions for patients with lung adenocarcinoma

The incidence of lung cancer, especially lung adenocarcinoma (LUAD), has recently increased. Targeted therapy and immunotherapy combined with conventional treatment have shown surprising benefits in enhancing the LUAD patient's prognosis. For the purpose of guiding treatment planning and the prognosis of LUAD, more research is required. The particular aim of this work was to establish a purine metabolism scoring (PMS) model for the purpose of individually forecasting treatment outcomes and overall survival for patients who have LUAD. Clinical and whole genome data were obtained from the TCGA-LUAD cohort via "UCSC". The 25 driver purine metabolism-related prognostic genes were determined founded on univariate Cox regression. Then PMS was developed through stepwise LASSO Cox regression. Survival analysis indicated that patients who have PMS experienced worse outcomes. We validated the PGM2 effect on lung adenocarcinoma malignancy in in vitro experiments. Univariate as well as multivariate Cox regression suggested that PMS was an independent prognostic indicator for LUAD patients, which was confirmed in subgroup analysis. Functional assay demonstrated that immune response as well as cytotoxicity pathways have a connection with lower PMS, and patients who have low PMS possess an active immune microenvironment. Moreover, the LUAD patients who have low PMS showed greater sensitivity to immunotherapy, targeted therapy, as well as chemotherapy. Knockdown of PGM2 was discovered to decrease the proliferation, invasion, as well as migration of lung adenocarcinoma cells in an in vitro assay. Pertaining to this particular research, we created a PMS model and conducted a thorough analysis of purine metabolism in LUAD in order to determine prognosis and offer recommendations for treatment. This finding offered a fresh concept for the clinical management of LUAD and novel therapy protocols.

KMT2A Mutations and High Prevalence of dMMR-associated Mutational Signatures as Prognostic Indicators in Metastatic Colorectal Cancer

The conventional treatment strategies for patients with metastatic colorectal cancer (mCRC) are predominantly guided by the status of RAS and BRAF mutations. Although patients may exhibit analogous pathological characteristics and undergo similar treatment regimens, notable disparities in their prognostic outcomes can be observed. Therefore, tissue and plasma samples from 40 mCRC patients underwent next-generation sequencing targeting 425 cancer-relevant genes. Genomic variations and canonical oncogenic pathways were investigated for their prognostic effects in association with progression-free survival (PFS) of these patients. We found that patients with BRCA2 and KMT2A mutations exhibited worse prognostic outcomes after chemotherapy-based treatment (univariate, P < 0.01). Further pathway analysis indicated that alterations in the homologous recombination pathway and in the KMT2A signaling network were also significantly associated with shortened PFS (univariate, P < 0.01). Additionally, mutation signature analysis showed that patients with higher proportions of defective mismatch repair (dMMR)-related mutational signatures. Had a worse prognosis (univariate, P = 0.02). KMT2A mutations (hazard ratio [HR], 4.47; 95% confidence interval [CI], 1-19.93; P =0.050) and dMMR signature proportions (HR, 3.57; 95% CI, 1.42-8.96; P = 0.007) remained independently associated with PFS after multivariate analysis and the results were further externally validated. These findings may enhance our understanding of this disease and may potentially facilitate the optimization of its treatment approaches.

Full-spectral genome analysis of natural killer/T cell lymphoma highlights impacts of genome instability in driving its progression

BACKGROUND

Natural killer/T cell lymphoma (NKTCL) is a clinically and genetically heterogeneous disease with poor prognosis. Genome sequencing and mutation characterization provides a powerful approach for patient stratification, treatment target discovery, and etiology identification. However, previous studies mostly concentrated on base-level mutations in primary NKTCL, whereas the large-scale genomic alterations in NKTCL and the mutational landscapes in relapsed/refractory NKTCL remain largely unexplored.

METHODS

Here, we assembled whole-genome sequencing and whole-exome sequencing data from 163 patients with primary or relapsed/refractory NKTCL and compared their somatic mutational landscapes at both nucleotide and structure levels.

RESULTS

Our study not only confirmed previously reported common NKTCL mutational targets like STAT3, TP53, and DDX3X but also unveiled several novel high-frequency mutational targets such as PRDM9, DST, and RBMX. In terms of the overall mutational landscape, we observed striking differences between primary and relapsed/refractory NKTCL patient groups, with the latter exhibits higher levels of tumor mutation burden, copy number variants (CNVs), and structural variants (SVs), indicating a strong signal of genomic instability. Complex structural rearrangements such as chromothripsis and focal amplification are also significantly enriched in relapsed/refractory NKTCL patients, exerting a substantial impact on prognosis. Accordingly, we devised a novel molecular subtyping system (i.e., C0-C4) with distinct prognosis by integrating potential driver mutations at both nucleotide and structural levels, which further provides an informative guidance for novel treatments that target these specific driver mutations and genome instability as a whole.

CONCLUSIONS

The striking differences underlying the mutational landscapes between the primary and relapsed/refractory NKTCL patients highlight the importance of genomic instability in driving the progression of NKTCL. Our newly proposed molecular subtyping system is valuable in assisting patient stratification and novel treatment design towards a better prognosis in the age of precision medicine.

Preliminary Analysis of Gut Microbiome and Gastrointestinal Symptom Burden in Breast Cancer Patients Receiving Chemotherapy Compared to Healthy Controls

BACKGROUND

Alterations in the naturally occurring bacteria of the gut, known as the gastrointestinal (GI) microbiome, may influence GI symptoms in women with breast cancer.

OBJECTIVE

This work aims to describe GI symptom occurrence, duration, severity, and distress and measures of the GI microbiome among women with breast cancer receiving chemotherapy compared to age- and sex-matched healthy controls.

INTERVENTIONS/METHODS

22 women with breast cancer receiving chemotherapy and 17 healthy control women provided stool specimens and GI symptom data using the modified Memorial Symptom Assessment Scale (MSAS). The fecal microbiome was profiled by metagenomic sequencing of 16S Ribosomal RNA (rRNA). GI microbiome was compared between groups using alpha-diversity (Observed OTU number and Shannon index), beta-diversity (UniFrac distances), and relative abundance of select genera.

RESULTS

GI symptoms with high symptom reports among breast cancer patients included nausea, diarrhea, flatulence, dry mouth, taste change, and poor appetite. Indices of differential abundance (beta diversity) significantly distinguished between breast cancer patients and healthy controls. Unique bacterial features differentiating the 2 groups were Prevotella_9, Akkermansia, Lachnospira, Lachnospiraceae_NK4A136, Lachnoclostridium, and Oscillibacter.

CONCLUSIONS

Gut bacteria are associated with GI inflammation and mucus degradation, suggesting the potential role of the GI microbiome in GI symptom burden. Understanding the influence of GI bacteria on gut health and symptoms will help harness the enormous potential of the GI microbiome as a future diagnostic and therapeutic agent to reduce the symptom burden associated with chemotherapy.

Multi-omic profiling of clear cell renal cell carcinoma identifies metabolic reprogramming associated with disease progression

Clear cell renal cell carcinoma (ccRCC) is a complex disease with remarkable immune and metabolic heterogeneity. Here we perform genomic, transcriptomic, proteomic, metabolomic and spatial transcriptomic and metabolomic analyses on 100 patients with ccRCC from the Tongji Hospital RCC (TJ-RCC) cohort. Our analysis identifies four ccRCC subtypes including De-clear cell differentiated (DCCD)-ccRCC, a subtype with distinctive metabolic features. DCCD cancer cells are characterized by fewer lipid droplets, reduced metabolic activity, enhanced nutrient uptake capability and a high proliferation rate, leading to poor prognosis. Using single-cell and spatial trajectory analysis, we demonstrate that DCCD is a common mode of ccRCC progression. Even among stage I patients, DCCD is associated with worse outcomes and higher recurrence rate, suggesting that it cannot be cured by nephrectomy alone. Our study also suggests a treatment strategy based on subtype-specific immune cell infiltration that could guide the clinical management of ccRCC.

Machine learning-based extrachromosomal DNA identification in large-scale cohorts reveals its clinical implications in cancer

The clinical implications of extrachromosomal DNA (ecDNA) in cancer therapy remain largely elusive. Here, we present a comprehensive analysis of ecDNA amplification spectra and their association with clinical and molecular features in multiple cohorts comprising over 13,000 pan-cancer patients. Using our developed computational framework, GCAP, and validating it with multifaceted approaches, we reveal a consistent pan-cancer pattern of mutual exclusivity between ecDNA amplification and microsatellite instability (MSI). In addition, we establish the role of ecDNA amplification as a risk factor and refine genomic subtypes in a cohort from 1015 colorectal cancer patients. Importantly, our investigation incorporates data from four clinical trials focused on anti-PD-1 immunotherapy, demonstrating the pivotal role of ecDNA amplification as a biomarker for guiding checkpoint blockade immunotherapy in gastrointestinal cancer. This finding represents clinical evidence linking ecDNA amplification to the effectiveness of immunotherapeutic interventions. Overall, our study provides a proof-of-concept of identifying ecDNA amplification from cancer whole-exome sequencing (WES) data, highlighting the potential of ecDNA amplification as a valuable biomarker for facilitating personalized cancer treatment.

Copy Number Alterations Predict Development of OSCC from Oral Leukoplakia

Oral leukoplakia (OLK) is a common type of potentially malignant disorder. Early identification of the malignancy potential leads to a better management of OLK and prediction of development of oral squamous cell carcinoma (OSCC). However, there has been no effective biomarker to assess the risk of malignancy in OLK. Genomic copy number alteration (CNA) is a complex chromosomal structural variation in the genome and has been identified as a potential biomarker in multiple cancers. This study aimed to develop a predictive model for the malignant transformation risk of OLK by copy number analysis. A total of 431 OLK samples with long-term follow-up (median follow-up of 67 mo) from multiple academic centers were analyzed for CNAs. CNA events increased with the severity of hyperplasia, mild dysplasia, moderate dysplasia, and severe dysplasia. More CNA events were present in patients with OLK who later developed OSCC than in those with OLK who did not. By multivariate Cox regression analysis, the OLK of the CNA scorehigh group showed an increased risk of malignant transformation than the CNA scorelow group (P < 0.001). A CNA score model was developed to accurately predict the prognosis (area under the receiver operating characteristic curve [AUC] = 0.879; 95% confidence interval [CI], 0.799-0.959) and was validated using data from 2 external centers (AUC = 0.836, 95% CI, 0.683-0.989; AUC = 0.876, 95% CI, 0.682-1.000), and all of them showed better prediction performances than histopathological grade in assessing the transformation risk of OLK. Furthermore, we performed CNA models among 4 subgroups of OLK with hyperplasia, mild dysplasia, moderate dysplasia, and severe dysplasia and found that CNA score can accurately predict malignant transformation of different subgroups. CNA score may be a useful biomarker to predict malignant transformation of OLK. Subtyping of OLK by the CNA score could contribute to better management of OLK and predicting development of OSCC.

Elevated incidence of somatic mutations at prevalent genetic sites

The common loci represent a distinct set of the human genome sites that harbor genetic variants found in at least 1% of the population. Small somatic mutations occur at the common loci and non-common loci, i.e. csmVariants and ncsmVariants, are presumed with similar probabilities. However, our work revealed that within the coding region, common loci constituted only 1.03% of all loci, yet they accounted for 5.14% of TCGA somatic mutations. Furthermore, the small somatic mutation incidence rate at these common loci was 2.7 times that observed in the non-common. Notably, the csmVariants exhibited an impressive recurrent rate of 36.14%, which was 2.59 times of the ncsmVariants. The C-to-T transition at the CpG sites accounted for 32.41% of the csmVariants, which was 2.93 times for the ncsmVariants. Interestingly, the aging-related mutational signature contributed to 13.87% of the csmVariants, 5.5 times that of ncsmVariants. Moreover, 35.93% of the csmVariants contexts exhibited palindromic features, outperforming ncsmVariant contexts by 1.84 times. Notably, cancer patients with higher csmVariants rates had better progression-free survival. Furthermore, cancer patients with high-frequency csmVariants enriched with mismatch repair deficiency were also associated with better progression-free survival. The accumulation of csmVariants during cancerogenesis is a complex process influenced by various factors. These include the presence of a substantial percentage of palindromic sequences at csmVariants sites, the impact of aging and DNA mismatch repair deficiency. Together, these factors contribute to the higher somatic mutation incidence rates of common loci and the overall accumulation of csmVariants in cancer development.

Evaluating topography of mutational signatures with SigProfilerTopography

The mutations found in a cancer genome are shaped by diverse processes, each displaying a characteristic mutational signature that may be influenced by the genome's architecture. While prior analyses have evaluated the effect of topographical genomic features on mutational signatures, there has been no computational tool that can comprehensively examine this interplay. Here, we present SigProfilerTopography, a Python package that allows evaluating the effect of chromatin organization, histone modifications, transcription factor binding, DNA replication, and DNA transcription on the activities of different mutational processes. SigProfilerTopography elucidates the unique topographical characteristics of mutational signatures, unveiling their underlying biological and molecular mechanisms.

[Mutational Signatures Analysis of Micropapillary Components and Exploration of ZNF469 Gene in Early-stage Lung Adenocarcinoma with Ground-glass Opacities]

BACKGROUND

In China, lung cancer remains the cancer with the highest incidence and mortality rate. Among early-stage lung adenocarcinomas (LUAD), the micropapillary (MPP) component is prevalent and typically exhibits high aggressiveness, significantly correlating with early metastasis, lymphatic infiltration, and reduced five-year survival rates. Therefore, the study is to explore the similarities and differences between MPP and non-micropapillary (non-MPP) components in malignant pulmonary nodules characterized by GGOs in early-stage LUAD, identify unique mutational features of the MPP component and analyze the relationship between the ZNF469 gene, a member of the zinc-finger protein family, and the prognosis of early-stage LUAD, as well as its correlation with immune infiltration.

METHODS

A total of 31 malignant pulmonary nodules of LUAD were collected and dissected into paired MPP and non-MPP components using microdissection. Whole-exome sequencing (WES) was performed on the components of early-stage malignant pulmonary nodules. Mutational signatures analysis was conducted using R packages such as maftools, Nonnegative Matrix Factorization (NMF), and Sigminer to unveil the genomic mutational characteristics unique to MPP components in invasive LUAD compared to other tumor tissues. Furthermore, we explored the expression of the ZNF469 gene in LUAD using The Cancer Genome Atlas (TCGA) database to investigate its potential association with the prognosis. We also investigated gene interaction networks and signaling pathways related to ZNF469 in LUAD using the GeneMANIA database and conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Lastly, we analyzed the correlation between ZNF469 gene expression and levels of immune cell infiltration in LUAD using the TIMER and TISIDB databases.

RESULTS

MPP components exhibited a higher number of genomic variations, particularly the 13th COSMIC (Catalogue of Somatic Mutations in Cancer) mutational signature characterized by the activity of the cytidine deaminase APOBEC family, which was unique to MPP components compared to non-MPP components in tumor tissues. This suggests the potential involvement of APOBEC in the progression of MPP components in early-stage LUAD. Additionally, MPP samples with high similarity to APOBEC signature displayed a higher tumor mutational burden (TMB), indicating that these patients may be more likely to benefit from immunotherapy. The expression of ZNF469 was significantly upregulated in LUAD compared to normal tissue, and was associated with poor prognosis in LUAD patients (P<0.05). Gene interaction network analysis and GO/KEGG enrichment analysis revealed that COL6A1, COL1A1, COL1A2, TGFB2, MMP2, COL8A2 and C2CD4C interacted with ZNF469 and were mainly involved in encoding collagen proteins and participating in the constitution of extracellular matrix. ZNF469 expression was positively correlated with immune cell infiltration in LUAD (P<0.05).

CONCLUSIONS

The study has unveiled distinctive mutational signatures in the MPP components of early-stage invasive LUAD in the Asian population. Furthermore, we have identified that the elevated expression of mutated ZNF469 impacts the prognosis and immune infiltration in LUAD, suggesting its potential as a diagnostic and prognostic biomarker in LUAD.

Comparison of the somatic genomic landscape between central- and peripheral-type non-small cell lung cancer

OBJECTIVE

Lung cancer is classified into central and peripheral types based on the anatomic location. The present study aimed to explore the distinct patterns of genomic alterations between central- and peripheral-type non-small cell lung cancers (NSCLCs) with negative driver genes and identify potential driver genes and biomarkers to improve therapy strategies for NSCLC.

METHODS

Whole-exome sequencing (WES) was performed with 182 tumor/control pairs of samples from 145 Chinese NSCLC patients without EGFR, ALK, or ROS1 alterations. Significantly mutated genes (SMGs) and somatic copy number alterations (SCNAs) were identified. Subsequently, tumor mutation burden (TMB), weighted genome integrity index (wGII), copy number alteration (CNA) burden, Shannon diversity index (SDI), intratumor heterogeneity (ITH), neoantigen load (NAL), and clonal variations were evaluated in central- and peripheral-type NSCLCs. Furthermore, mutational signature analysis and survival analysis were performed.

RESULTS

TP53 was the most frequently mutated gene in NSCLC and more frequently mutated in central-type NSCLC. Higher wGII, ITH, and SDI were found in central-type lung adenocarcinoma (LUAD) than in peripheral-type LUAD. The NAL of central-type lung squamous cell carcinoma (LUSC) with stage III/IV was significantly higher than that of peripheral-type LUSC. Mutational signature analysis revealed that SBS10b, SBS24, and ID7 were significantly different in central- and peripheral-type NSCLCs. Furthermore, central-type NSCLC was found to evolve at a higher level with fewer clones and more subclones, particularly in central-type LUSC. Survival analysis revealed that TMB, CNA burden, NAL, subclonal driver mutations, and subclonal mutations were negatively related to the overall survival (OS) and the progression-free survival (PFS) of central-type LUAD.

CONCLUSIONS

Central-type NSCLC tended to evolve at a higher level and might suggest a favorable response to immunotherapy. Our study also identified several potential driver genes and promising biomarkers for the prognosis and prediction of chemotherapy responses in NSCLC.

Association between copy number alterations estimated using low-pass whole genome sequencing of formalin-fixed paraffin-embedded prostate tumor tissue and cancer-specific clinical parameters

Copy number alterations (CNAs) are frequently observed in early-stage prostate cancer and are associated with disease recurrence and tumor aggressiveness. Cost-effective assessment of CNAs could enhance clinical utility of CNAs. Here, we combined the cost-effectiveness of low-pass (low coverage) whole genome sequencing (LPWGS) and the routine availability of formalin-fixed paraffin-embedded (FFPE) tumor tissue for assessing CNAs in a cohort of 187 men with early-stage localised prostate cancer. We detected well known CNAs in 8p, 8q, 13q and 16q and recurrent gains of the oncogene MYC and losses of the tumor suppressor genes NKX3-1, PTEN and RB1, indicating assay reliability. The estimated burden of CNAs was significantly associated with Gleason score, pathological T stage, surgical margin status and biochemical recurrence. Further, genomic losses or gains in specific chromosomal arms were significantly associated with worse BCR-free survival. Copy number signatures extracted from the LPWGS data showed potential for risk stratifying patients, where signatures S1 and S2 showed significant association to worse BCR-free survival compared to S3. Our study provides clinical validation of the associations between CNAs and tumor aggressiveness in an independent and representative RP cohort, while demonstrating the feasibility of performing LPWGS of FFPE tumor tissue for cost-effective assessment of CNAs.

Mitochondrial DNA Variants at Low-Level Heteroplasmy and Decreased Copy Numbers in Chronic Kidney Disease (CKD) Tissues with Kidney Cancer

The human mitochondrial genome (mtDNA) is a circular DNA molecule with a length of 16.6 kb, which contains a total of 37 genes. Somatic mtDNA mutations accumulate with age and environmental exposure, and some types of mtDNA variants may play a role in carcinogenesis. Recent studies observed mtDNA variants not only in kidney tumors but also in adjacent kidney tissues, and mtDNA dysfunction results in kidney injury, including chronic kidney disease (CKD). To investigate whether a relationship exists between heteroplasmic mtDNA variants and kidney function, we performed ultra-deep sequencing (30,000×) based on long-range PCR of DNA from 77 non-tumor kidney tissues of kidney cancer patients with CKD (stages G1 to G5). In total, this analysis detected 697 single-nucleotide variants (SNVs) and 504 indels as heteroplasmic (0.5% ≤ variant allele frequency (VAF) < 95%), and the total number of detected SNVs/indels did not differ between CKD stages. However, the number of deleterious low-level heteroplasmic variants (pathogenic missense, nonsense, frameshift and tRNA) significantly increased with CKD progression (p < 0.01). In addition, mtDNA copy numbers (mtDNA-CNs) decreased with CKD progression (p < 0.001). This study demonstrates that mtDNA damage, which affects mitochondrial genes, may be involved in reductions in mitochondrial mass and associated with CKD progression and kidney dysfunction.

Prognostic potential of whole exome sequencing in the clinical management of metachronous colorectal cancer liver metastases

BACKGROUND

Colorectal cancer is a highly prevalent and deadly. The most common metastatic site is the liver. We performed a whole exome sequencing analysis of a series of metachronous colorectal cancer liver metastases (mCLM) and matched non-malignant liver tissues to investigate the genomic profile of mCLM and explore associations with the patients' prognosis and therapeutic modalities.

METHODS

DNA samples from mCLM and non-malignant liver tissue pairs (n = 41) were sequenced using whole exome target enrichment and their germline and somatic genetic variability, copy number variations, and mutational signatures were assessed for associations with relapse-free (RFS) and overall survival (OS).

RESULTS

Our genetic analysis could stratify all patients into existing targeted therapeutic regimens. The most commonly mutated genes in mCLM were TP53, APC, and KRAS together with PIK3CA and several passenger genes like ABCA13, FAT4, PCLO, and UNC80. Patients with somatic alterations in genes from homologous recombination repair, Notch, and Hedgehog pathways had significantly prolonged RFS, while those with altered MYC pathway genes had poor RFS. Additionally, alterations in the JAK-STAT pathway were prognostic of longer OS. Patients bearing somatic variants in VIPR2 had significantly shorter OS and those with alterations in MUC16 prolonged OS. Carriage of the KRAS-12D variant was associated with shortened survival in our and external datasets. On the other hand, tumor mutation burden, mismatch repair deficiency, microsatellite instability, mutational signatures, or copy number variation in mCLM had no prognostic value.

CONCLUSIONS

The results encourage further molecular profiling for personalized treatment of colorectal cancer liver metastases discerning metachronous from synchronous scenarios.

Integrative whole-genome and transcriptome analysis of HER2-amplified metastatic breast cancer

BACKGROUND

In breast cancer, the advent of anti-HER2 therapies has made HER2+ tumors a highly relevant subgroup. However, the exact characteristics which prohibit clinical response to anti-HER2 therapies and drive disease progression are not yet fully known. Integrative whole-genome and transcriptomic sequencing data from both primary and metastatic HER2-positive breast cancer will enhance our understanding of underlying biological processes.

METHODS

Here, we used WGS and RNA sequencing data of 700 metastatic breast tumors, of which 68 being HER2+, to search for specific genomic features of HER2+ disease and therapy resistance. Furthermore, we integrated results with transcriptomic data to associate tumors exhibiting a HER2+-specific gene expression profile with ERBB2 mutation status, prior therapy and relevant gene expression signatures.

RESULTS

Overall genomic profiles of primary and metastatic HER2+ breast cancers were similar, and no specific acquired genomics traits connected to prior anti-HER2 treatment were observed. However, specific genomic features were predictive of progression-free survival on post-biopsy anti-HER2 treatment. Furthermore, a HER2-driven expression profile grouped HER2-amplified tumors with ERBB2-mutated cases and cases without HER2 alterations. The latter were reported as ER positive in primary disease, but the metastatic biopsy showed low ESR1 expression and upregulation of the MAPK pathway, suggesting transformation to ER independence.

CONCLUSIONS

In summary, although the quantity of variants increased throughout HER2-positive breast cancer progression, the genomic composition remained largely consistent, thus yielding no new major processes beside those already operational in primary disease. Our results suggest that integrated genomic and transcriptomic analyses may be key in establishing therapeutic options.

Multi-scale characterisation of homologous recombination deficiency in breast cancer

BACKGROUND

Homologous recombination is a robust, broadly error-free mechanism of double-strand break repair, and deficiencies lead to PARP inhibitor sensitivity. Patients displaying homologous recombination deficiency can be identified using 'mutational signatures'. However, these patterns are difficult to reliably infer from exome sequencing. Additionally, as mutational signatures are a historical record of mutagenic processes, this limits their utility in describing the current status of a tumour.

METHODS

We apply two methods for characterising homologous recombination deficiency in breast cancer to explore the features and heterogeneity associated with this phenotype. We develop a likelihood-based method which leverages small insertions and deletions for high-confidence classification of homologous recombination deficiency for exome-sequenced breast cancers. We then use multinomial elastic net regression modelling to develop a transcriptional signature of heterogeneous homologous recombination deficiency. This signature is then applied to single-cell RNA-sequenced breast cancer cohorts enabling analysis of homologous recombination deficiency heterogeneity and differential patterns of tumour microenvironment interactivity.

RESULTS

We demonstrate that the inclusion of indel events, even at low levels, improves homologous recombination deficiency classification. Whilst BRCA-positive homologous recombination deficient samples display strong similarities to those harbouring BRCA1/2 defects, they appear to deviate in microenvironmental features such as hypoxic signalling. We then present a 228-gene transcriptional signature which simultaneously characterises homologous recombination deficiency and BRCA1/2-defect status, and is associated with PARP inhibitor response. Finally, we show that this signature is applicable to single-cell transcriptomics data and predict that these cells present a distinct milieu of interactions with their microenvironment compared to their homologous recombination proficient counterparts, typified by a decreased cancer cell response to TNFα signalling.

CONCLUSIONS

We apply multi-scale approaches to characterise homologous recombination deficiency in breast cancer through the development of mutational and transcriptional signatures. We demonstrate how indels can improve homologous recombination deficiency classification in exome-sequenced breast cancers. Additionally, we demonstrate the heterogeneity of homologous recombination deficiency, especially in relation to BRCA1/2-defect status, and show that indications of this feature can be captured at a single-cell level, enabling further investigations into interactions between DNA repair deficient cells and their tumour microenvironment.

Chromosome instability region analysis and identification of the driver genes of the epithelial ovarian cancer cell lines A2780 and SKOV3

Epithelial ovarian cancer (EOC) is one of the most prevalent gynaecological cancers worldwide. The molecular mechanisms of serous ovarian cancer (SOC) remain unclear and not well understood. SOC cases are primarily diagnosed at the late stage, resulting in a poor prognosis. Advances in molecular biology techniques allow us to obtain a better understanding of precise molecular mechanisms and to identify the chromosome instability region and key driver genes in the carcinogenesis and progression of SOC. Whole-exome sequencing was performed on the normal ovarian cell line IOSE80 and the EOC cell lines SKOV3 and A2780. The single-nucleotide variation burden, distribution, frequency and signature followed the known ovarian mutation profiles, without chromosomal bias. Recurrently mutated ovarian cancer driver genes, including LRP1B, KMT2A, ARID1A, KMT2C and ATRX were also found in two cell lines. The genome distribution of copy number alterations was found by copy number variation (CNV) analysis, including amplification of 17q12 and 4p16.1 and deletion of 10q23.33. The CNVs of MED1, GRB7 and MIEN1 located at 17q12 were found to be correlated with the overall survival of SOC patients (MED1: p = 0.028, GRB7: p = 0.0048, MIEN1: p = 0.0051), and the expression of the three driver genes in the ovarian cell line IOSE80 and EOC cell lines SKOV3 and A2780 was confirmed by western blot and cell immunohistochemistry.

Sequential genomic analysis using a multisample/multiplatform approach to better define rhabdomyosarcoma progression and relapse

The genomic spectrum of rhabdomyosarcoma (RMS) progression from primary to relapse is not fully understood. In this pilot study, we explore the sensitivity of various targeted and whole-genome NGS platforms in order to assess the best genomic approach of using liquid biopsy in future prospective clinical trials. Moreover, we investigate 35 paired primary/relapsed RMS from two contributing institutions, 18 fusion-positive (FP-RMS) and 17 fusion-negative RMS (FN-RMS) by either targeted DNA or whole exome sequencing (WES). In 10 cases, circulating tumor DNA (ctDNA) from multiple timepoints through clinical care and progression was analyzed for feasibility of liquid biopsy in monitoring treatment response/relapse. ctDNA alterations were evaluated using a targeted 36-gene custom RMS panel at high coverage for single-nucleotide variation and fusion detection, and a shallow whole-genome sequencing for copy number variation. FP-RMS have a stable genome with relapse, with common secondary alterations CDKN2A/B, MYCN, and CDK4 present at diagnosis and impacting survival. FP-RMS lacking major secondary events at baseline acquire recurrent MYCN and AKT1 alterations. FN-RMS acquire a higher number of new alterations, most commonly SMARCA2 missense mutations. ctDNA analyses detect pathognomonic variants in all RMS patients within our collection at diagnosis, regardless of type of alterations, and confirmed at relapse in 86% of FP-RMS and 100% FN-RMS. Moreover, a higher number of fusion reads is detected with increased disease burden and at relapse in patients following a fatal outcome. These results underscore patterns of tumor progression and provide rationale for using liquid biopsy to monitor treatment response.

Identification of lncRNAs associated with T cells as potential biomarkers and therapeutic targets in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common and deadliest subtype of lung cancer. To select more targeted and effective treatments for individuals, further advances in classifying LUAD are urgently needed. The number, type, and function of T cells in the tumor microenvironment (TME) determine the progression and treatment response of LUAD. Long noncoding RNAs (lncRNAs), may regulate T cell differentiation, development, and activation. Thus, our aim was to identify T cell-related lncRNAs (T cell-Lncs) in LUAD and to investigate whether T cell-Lncs could serve as potential stratifiers and therapeutic targets. Seven T cell-Lncs were identified to further establish the T cell-related lncRNA risk score (TRS) in LUAD. Low TRS individuals were characterized by robust immune status, fewer genomic alterations, and remarkably longer survival than high TRS individuals. The excellent accuracy of TRS in predicting overall survival (OS) was validated in the TCGA-LUAD training cohort and the GEO-LUAD validation cohort. Our data demonstrated the favorable predictive power of the TRS-based nomogram, which had important clinical significance in estimating the survival probability for individuals. In addition, individuals with low TRS could respond better to chemotherapy and immunotherapy than those with high TRS. LINC00525 was identified as a valuable study target, and the ability of LUAD to proliferate or invade was significantly attenuated by downregulation of LINC00525. In conclusion, the TRS established by T cell-Lncs could unambiguously classify LUAD patients, predict their prognosis and guide their management. Moreover, our identified T cell-Lncs could provide potential therapeutic targets for LUAD.

Pan-Cancer Analysis of Copy-Number Features Identifies Recurrent Signatures and a Homologous Recombination Deficiency Biomarker to Predict Poly (ADP-Ribose) Polymerase Inhibitor Response

PURPOSE

Copy-number (CN) features reveal the molecular state of cancers and may have predictive and prognostic value in the treatment of cancer. We sought to apply published CN analysis methods to a large pan-cancer data set and characterize ubiquitous CN signatures across tumor types, including potential utility for treatment selection.

METHODS

We analyzed the landscape of CN features in 260,333 pan-cancer samples. We examined the association of 10 signatures with genomic alterations and clinical characteristics and trained a machine learning classifier using CN and insertion and deletion features to detect homologous recombination deficiency signature (HRDsig) positivity. Clinical outcomes were assessed using a real-world clinicogenomic database (CGDB) of comprehensive genomic profiling linked to deidentified, electronic health record-derived clinical data.

RESULTS

CN signatures were prevalent across cancer types and associated with diverse processes including focal tandem duplications, seismic amplifications, genome-wide loss of heterozygosity (gLOH), and HRD. Our novel HRDsig outperformed gLOH in predicting BRCAness and effectively distinguished biallelic BRCA and homologous recombination-repair wild-type (HRRwt) samples pan-tumor, demonstrating high sensitivity to detect biallelic BRCA in ovarian (93%) and other HRD-associated cancers (80%-87%). Pan-tumor prevalence of HRDsig was 6.4%. HRRwt cases represented a significant fraction of the HRDsig-positive cohort, likely reflecting a population with nongenomic mechanisms of HRD. In ovarian and prostate CGDBs, HRDsig identified more patients than gLOH and had predictive value for poly (ADP-ribose) polymerase inhibitor (PARPi) benefit.

CONCLUSION

Tumor CN profiles are informative, revealing diverse processes active in cancer. We describe the landscape of 10 CN signatures in a large pan-cancer cohort, including two associated with HRD. We trained a machine learning-based HRDsig that robustly identified BRCAness and associated with biallelic BRCA pan-tumor, and was predictive of PARPi benefit in real-world ovarian and prostate data sets.

Clonal dynamics and Stereo-seq resolve origin and phenotypic plasticity of adenosquamous carcinoma

The genomic origin and development of the biphasic lung adenosquamous carcinoma (ASC) remain inconclusive. Here, we derived potential evolutionary trajectory of ASC through whole-exome sequencing, Stereo-seq, and patient-derived xenografts. We showed that EGFR and MET activating mutations were the main drivers in ASCs. Phylogenetically, these drivers and passenger mutations found in both components were trunk clonal events, confirming monoclonal origination. Comparison of multiple lesions also revealed closer genomic distance between lymph node metastases and the ASC component with the same phenotype. However, as mutational signatures of EGFR-positive lung squamous carcinomas (LUSCs) were more comparable to EGFR-positive ASCs than to wild-type LUSCs, we postulated different origination of these LUSCs, with ASC being the potential intermediate state of driver-positive LUSCs. Spatial transcriptomic profiling inferred transformation from adenocarcinoma to squamous cell carcinoma, which was then histologically captured in vivo. Together, our results explained the development of ASC and provided insights into future clinical decisions.

Identification of hepatocellular carcinoma-related subtypes and development of a prognostic model: a study based on ferritinophagy-related genes

BACKGROUND

Hepatocellular carcinoma still has a high incidence and mortality rate worldwide, and further research is needed to investigate its occurrence and development mechanisms in depth in order to identify new therapeutic targets. Ferritinophagy is a type of autophagy and a key factor in ferroptosis that could influence tumor onset and progression. Although, the potential role of ferritinophagy-related genes (FRGs) in liver hepatocellular carcinoma (LIHC) is unknown.

METHODS

Single-cell RNA sequencing (scRNA-seq) data of LIHC were obtained from the Gene Expression Omnibus (GEO) dataset. In addition, transcriptome and clinical follow-up outcome data of individuals with LIHC were extracted from the The Cancer Genome Atlas (TCGA) dataset. FRGs were collected through the GeneCards database. Differential cell subpopulations were distinguished, and differentially expressed FRGs (DEFRGs) were obtained. Differential expression of FRGs and prognosis were observed according to the TCGA database. An FRG-related risk model was constructed to predict patient prognosis by absolute shrinkage and selection operator (LASSO) and COX regression analyses, and its prognosis predictive power was validated. Ultimately, the association between risk score and tumor microenvironment (TME), immune cell infiltration, immune checkpoints, drug sensitivity, and tumor mutation burden (TMB) was analyzed. We also used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to validate the expression of key genes in normal liver cells and liver cancer cells.

RESULTS

We ultimately identified 8 cell types, and 7 differentially expressed FRGs genes (ZFP36, NCOA4, FTH1, FTL, TNF, PCBP1, CYB561A3) were found among immune cells, and we found that Monocytes and Macrophages were closely related to FRGs genes. Subsequently, COX regression analysis showed that patients with high expression of FTH1, FTL, and PCBP1 had significantly worse prognosis than those with low expression, and our survival prediction model, constructed based on age, stage, and risk score, showed better prognostic prediction ability. Our risk model based on 3 FRGs genes ultimately revealed significant differences between high-risk and low-risk groups in terms of immune infiltration and immune checkpoint correlation, drug sensitivity, and somatic mutation risk. Finally, we validated the key prognostic genes FTH1, FTL, using qRT-PCR, and found that the expression of FTH1 and FTL was significantly higher in various liver cancer cells than in normal liver cells. At the same time, immunohistochemistry showed that the expression of FTH1, FTL in tumor tissues was significantly higher than that in para-tumor tissues.

CONCLUSION

This study identifies a considerable impact of FRGs on immunity and prognosis in individuals with LIHC. The collective findings of this research provide new ideas for personalized treatment of LIHC and a more targeted therapy approach for individuals with LIHC to improve their prognosis.

Distinct genomic landscapes in radiation-associated angiosarcoma compared with other radiation-associated sarcoma histologies

MYC amplifications have been frequently detected in radiation (RT)-associated angiosarcomas (ASs) by low-resolution molecular methods. However, large-scale next-generation sequencing (NGS) studies to investigate the genomic landscape of RT-AS are scarce, particularly compared with other RT-associated sarcomas. We performed a detailed comparative genomic investigation of RT-AS versus other RT-associated histotypes, as well as sporadic sarcomas with similar histologies. Our institutional targeted DNA-NGS assay database was searched for RT-associated sarcomas. Clinical outcome data, pathologic diagnosis, and the types and frequencies of genomic alterations, including single nucleotide variants (SNVs) and copy number alterations (CNAs), were analyzed. The cohort consisted of 82 patients, 68 (83%) females and 14 (17%) males, aged 37-88 (mean 64) years. Forty-four RT-ASs (38 from breast) and 38 RT sarcomas of other histologies, including 12 malignant peripheral nerve sheath tumors (RT-MPNSTs), 14 undifferentiated pleomorphic sarcomas (RT-UPSs), and 12 osteosarcomas (RT-OSs), were included. Median time intervals from radiation to initial diagnosis in RT-AS (8.0 years) were significantly lower than those in RT-MPNST and RT-UPS (12.5 and 18.5 years), respectively. Each RT-sarcoma histotype harbored distinct mutations and CNAs. RT-associated AS had more frequent MYC, FLT4, CRKL, HRAS, and KMT2D alterations than sporadic AS (enriched in TP53, KDR, ATM, ATRX), whereas the mutational landscapes of MPNST, UPS, and OS were similar in both RT and non-RT settings. CDKN2A/B deletions and TP53 alterations were infrequent in RT-AS compared with other RT sarcomas. Among RT sarcomas, RT-AS harbored the lowest fraction of genome altered (FGA), while RT-MPNST showed the highest FGA. RT-AS had the lowest insertion:SNV and deletion:SNV ratios, while RT-UPS had the highest. The predominant mutational signatures were associated with errors in DNA repair and replication. In conclusion, RT-AS has a distinct genomic landscape compared with other RT sarcomas and sporadic AS. Potential molecular targets for precision medicine may be histotype-dependent. © 2023 The Pathological Society of Great Britain and Ireland.

Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma

A variety of mutational processes drive cancer development, but their dynamics across the entire disease spectrum from pre-cancerous to advanced neoplasia are poorly understood. We explore the mutagenic processes shaping oesophageal adenocarcinoma tumorigenesis in 997 instances comprising distinct stages of this malignancy, from Barrett Oesophagus to primary tumours and advanced metastatic disease. The mutational landscape is dominated by the C[T > C/G]T substitution enriched signatures SBS17a/b, which are linked with TP53 mutations, increased proliferation, genomic instability and disease progression. The APOBEC mutagenesis signature is a weak but persistent signal amplified in primary tumours. We also identify prevalent alterations in DNA damage repair pathways, with homologous recombination, base and nucleotide excision repair and translesion synthesis mutated in up to 50% of the cohort, and surprisingly uncoupled from transcriptional activity. Among these, the presence of base excision repair deficiencies show remarkably poor prognosis in the cohort. In this work, we provide insights on the mutational aetiology and changes enabling the transition from pre-neoplastic to advanced oesophageal adenocarcinoma.

A DNA copy number alteration classifier as a prognostic tool for prostate cancer patients

BACKGROUND

Distinguishing between true indolent and potentially life-threatening prostate cancer is challenging in tumours displaying clinicopathologic features associated with low or intermediate risk of relapse. Several somatic DNA copy number alterations (CNAs) have been identified as potential prognostic biomarkers, but the standard cytogenetic method to assess them has a limited multiplexing capability.

METHODS

Multiplex ligation-dependent probe amplification (MLPA) targeting 14 genes was optimised to survey 448 tumours of patients with low or intermediate risk (Grade Group 1-3, Gleason score ≤7) who underwent radical prostatectomy. A 6-gene CNA classifier was developed using random survival forest and Cox proportional hazard modelling to predict biochemical recurrence.

RESULTS

The classifier score was significantly associated with biochemical recurrence after adjusting for standard clinicopathologic variables and the known prognostic index CAPRA-S score with a hazard ratio of 2.17 and 1.80, respectively (n = 406, P < 0.01). The prognostic value of this classifier was externally validated in published CNA data from three radical prostatectomy cohorts and one radiation therapy pre-treatment biopsy cohort.

CONCLUSION

The 6-gene CNA classifier generated by a single MLPA assay compatible with the small quantities of DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissue specimens has the potential to improve the clinical management of patients with low or intermediate risk disease.

Copy number alteration features in pan-cancer homologous recombination deficiency prediction and biology

Homologous recombination deficiency (HRD) renders cancer cells vulnerable to unrepaired double-strand breaks and is an important therapeutic target as exemplified by the clinical efficacy of poly ADP-ribose polymerase (PARP) inhibitors as well as the platinum chemotherapy drugs applied to HRD patients. However, it remains a challenge to predict HRD status precisely and economically. Copy number alteration (CNA), as a pervasive trait of human cancers, can be extracted from a variety of data sources, including whole genome sequencing (WGS), SNP array, and panel sequencing, and thus can be easily applied clinically. Here we systematically evaluate the predictive performance of various CNA features and signatures in HRD prediction and build a gradient boosting machine model (HRD_CNA) for pan-cancer HRD prediction based on these CNA features. CNA features BP10MB[1] (The number of breakpoints per 10MB of DNA is 1) and SS[ > 7 & <=8] (The log10-based size of segments is greater than 7 and less than or equal to 8) are identified as the most important features in HRD prediction. HRD_CNA suggests the biallelic inactivation of BRCA1, BRCA2, PALB2, RAD51C, RAD51D, and BARD1 as the major genetic basis for human HRD, and may also be applied to effectively validate the pathogenicity of BRCA1/2 variants of uncertain significance (VUS). Together, this study provides a robust tool for cost-effective HRD prediction and also demonstrates the applicability of CNA features and signatures in cancer precision medicine.

An immunogenic and oncogenic feature-based classification for chemotherapy plus PD-1 blockade in advanced esophageal squamous cell carcinoma

Although chemotherapy plus PD-1 blockade (chemo+anti-PD-1) has become the standard first-line therapy for advanced esophageal squamous cell carcinoma (ESCC), reliable biomarkers for this regimen are lacking. Here we perform whole-exome sequencing on tumor samples from 486 patients of the JUPITER-06 study and develop a copy number alteration-corrected tumor mutational burden that depicts immunogenicity more precisely and predicts chemo+anti-PD-1 efficacy. We identify several other favorable immunogenic features (e.g., HLA-I/II diversity) and risk oncogenic alterations (e.g., PIK3CA and TET2 mutation) associated with chemo+anti-PD-1 efficacy. An esophageal cancer genome-based immuno-oncology classification (EGIC) scheme incorporating these immunogenic features and oncogenic alterations is established. Chemo+anti-PD-1 achieves significant survival improvements in EGIC1 (immunogenic feature-favorable and oncogenic alteration-negative) and EGIC2 (either immunogenic feature-favorable or oncogenic alteration-negative) subgroups, but not the EGIC3 subgroup (immunogenic feature-unfavorable and oncogenic alteration-positive). Thus, EGIC may guide future individualized treatment strategies and inform mechanistic biomarker research for chemo+anti-PD-1 treatment in patients with advanced ESCC.

Multi-omics profiling of papillary thyroid microcarcinoma reveals different somatic mutations and a unique transcriptomic signature

BACKGROUND

Papillary thyroid microcarcinoma (PTMC) incidence has significantly increased, and some cases still exhibit invasive traits. The entire molecular landscape of PTMC, which can offer hints for the etiology of cancer, is currently absent.

METHODS

We compared our findings with those for PTMC in the TCGA by analyzing the largest study at the current stage of whole exome sequencing and RNA-sequencing data from 64 patients with PTMC. Then, we systematically demonstrated the differences between the two PTMC subtypes based on multi-omics analyses. Additionally, we created a molecular prediction model for the PTMC subtypes and validated them among TCGA patients for individualized integrative assessment.

RESULTS

In addition to the presence of BRAF mutations and RET fusions in the TCGA cohort, we also discovered a new molecular signature named PTMC-inflammatory that implies a potential response to immune intervention, which is enriched with AFP mutations, IGH@-ext fusions, elevated immune-related genes, positive peroxidase antibody, and positive thyroglobulin antibody. Additionally, a molecular prediction model for the PTMC-inflammatory patients was created and validated among TCGA patients, while the prognosis for these patients is poor.

CONCLUSIONS

Our findings comprehensively define the clinical and molecular features of PTMC and may inspire new therapeutic hypotheses.

The repertoire of copy number alteration signatures in human cancer

Copy number alterations (CNAs) are a predominant source of genetic alterations in human cancer and play an important role in cancer progression. However comprehensive understanding of the mutational processes and signatures of CNA is still lacking. Here we developed a mechanism-agnostic method to categorize CNA based on various fragment properties, which reflect the consequences of mutagenic processes and can be extracted from different types of data, including whole genome sequencing (WGS) and single nucleotide polymorphism (SNP) array. The 14 signatures of CNA have been extracted from 2778 pan-cancer analysis of whole genomes WGS samples, and further validated with 10 851 the cancer genome atlas SNP array dataset. Novel patterns of CNA have been revealed through this study. The activities of some CNA signatures consistently predict cancer patients' prognosis. This study provides a repertoire for understanding the signatures of CNA in cancer, with potential implications for cancer prognosis, evolution and etiology.

Hereditary cancer variants and homologous recombination deficiency in biliary tract cancer

BACKGROUND & AIMS

The heritability and actionability of variants in homologous recombination-related genes in biliary tract cancers (BTCs) are uncertain. Although associations between BTC and BRCA germline variants have been reported, homologous recombination deficiency has not been investigated in BTCs.

METHODS

We sequenced germline variants in 27 cancer-predisposing genes in 1,292 BTC cases and 37,583 controls without a personal nor family history of cancer. We compared pathogenic germline variant frequencies between cases and controls and documented the demographic and clinical characteristics of carriers. In addition, whole-genome sequencing of 45 BTC tissues was performed to evaluate homologous recombination deficiency status.

RESULTS

Targeted sequencing identified 5,018 germline variants, which were classified into 317 pathogenic, 3,611 variants of uncertain significance, and 1,090 benign variants. Seventy-one BTC cases (5.5%) had at least one pathogenic variant among 27 cancer-predisposing genes. Pathogenic germline variants enriched in BTCs were present in BRCA1, BRCA2, APC, and MSH6 (p <0.00185). PALB2 variants were marginally associated with BTC (p = 0.01). APC variants were predominantly found in ampulla of Vater carcinomas. Whole-genome sequencing demonstrated that three BTCs with pathogenic germline variants in BRCA2 and PALB2, accompanied by loss of heterozygosity, displayed homologous recombination deficiency. Conversely, pathogenic germline variants without a second hit or variants of other homologous recombination-related genes such as ATM and BRIP1 showed homologous recombination-proficient phenotypes.

CONCLUSIONS

In this study, we describe the heritability and actionability of variants in homologous recombination-related genes, which could be used to guide screening and therapeutic strategies for BTCs.

IMPACT AND IMPLICATIONS

We found that 5.5% of biliary tract cancers (BTCs) in a Japanese population possessed hereditary cancer-predisposing gene alterations, including in BRCA and genes associated with colorectal cancer. Two hits in homologous recombination-related genes were required to confer a homologous recombination-deficient phenotype. PARP inhibitors and DNA-damaging regimens may be effective strategies against BTCs exhibiting homologous recombination deficiency. Hence, in this study, genome-wide sequencing has revealed a potential new therapeutic strategy that could be applied to a subset of BTCs.