Tumor copy number alteration burden is a pan-cancer prognostic factor associated with recurrence and death

Targeting WEE1 kinase as a therapeutic strategy in ATIP3-deficient breast cancers

ATIP3-deficient breast cancers represent a subset of aggressive tumors with limited therapeutic options and poor prognosis. Here, we screened a panel of cell cycle kinase inhibitors to identify novel targets for these tumors. We show that loss of ATIP3 sensitizes breast cancer cells to WEE1 inhibition, resulting in aberrant mitoses characterized by detachment of centromere proteins from DNA and chromosome pulverization. This phenotype arises from excessive replication stress and DNA damage in S-phase, combined with premature mitotic entry driven by untimely CDK1 activation. Mechanistically, we identify DNA2 helicase/nuclease as a key mediator of chromosome pulverization. Importantly, the heightened sensitivity of ATIP3-deficient cells to WEE1 inhibition provides a strong rationale for clinical exploration of WEE1-targeted therapies. Furthermore, combining WEE1 and PKMYT1 inhibitors enhances therapeutic efficacy, offering a promising strategy for personalized treatment in ATIP3-deficient breast cancers.

Colibactin Exerts Androgen-dependent and -independent Effects on Prostate Cancer

BACKGROUND AND OBJECTIVE

The etiology of prostate cancer (PC) is multifactorial and poorly understood. It has been suggested that colibactin-producing Escherichia coli positive for the pathogenicity island pks (pks+) initiate cancers via induction of genomic instability. In PC, androgens promote oncogenic translocations. Our aim was to investigate the association of pks+E. coli with PC diagnosis and molecular architecture, and its relationship with androgens.

METHODS

We quantified the association of pks+E. coli with PC diagnosis in a volunteer-sampled 235-person cohort from two institutional practices (UT San Antonio). We then used colibactin 742 and DNA/RNA sequencing to evaluate the effects of colibactin 742, dihydrotestosterone (DHT), and their combination in vitro.

KEY FINDINGS AND LIMITATIONS

Colibactin exposure was positively associated with PC diagnosis (p = 0.04) in our clinical cohort, and significantly increased replication fork stalling and fusions in vitro (p < 0.01). Combined in vitro exposure to colibactin 742 and DHT induced more somatic mutations of all types than exposure to either alone. The combination also elicited kataegis, with a higher density of somatic point mutations. Laboratory analyses were conducted using a single cell line, which limited our ability to fully recapitulate the complexity of PC etiology.

CONCLUSIONS AND CLINICAL IMPLICATIONS

Our findings are consistent with synergistic induction of genome instability and kataegis by colibactin 742 and DHT in cell culture. Colibactin-producing pks+ E. coli may plausibly contribute to PC etiology.

PATIENT SUMMARY

We investigated whether a bacterial toxin that is linked to colon cancer can also cause prostate cancer. Our results support this idea by showing a link between the toxin and prostate cancer diagnosis in a large patient population. We also found that this toxin causes genetic dysfunction in prostate cancer cells when combined with testosterone.

Nanopore-based consensus sequencing enables accurate multimodal tumor cell-free DNA profiling

Shallow genome-wide cell-free DNA sequencing holds great promise for noninvasive cancer monitoring by providing reliable copy number alteration (CNA) and fragmentomic profiles. Single-nucleotide variations (SNVs) are, however, much harder to identify with low sequencing depth due to sequencing errors. Here, we present Nanopore Rolling Circle Amplification (RCA)-enhanced Consensus Sequencing (NanoRCS), which leverages RCA and consensus calling based on genome-wide long-read nanopore sequencing to enable simultaneous multimodal tumor fraction (TF) estimation through SNVs, CNAs, and fragmentomics. The efficacy of NanoRCS is tested on 18 cancer patient samples and seven healthy controls, demonstrating its ability to reliably detect TFs as low as 0.24%. In vitro experiments confirm that SNV measurements are essential for detecting TFs below 3%. NanoRCS provides an opportunity for cost-effective and rapid sample processing, which aligns well with clinical needs, particularly in settings where quick and accurate cancer monitoring is essential for personalized treatment strategies.

Proteogenomic discovery of RB1-defective phenocopy in cancer predicts disease outcome, response to treatment, and therapeutic targets

Genomic defects caused by truncating mutations or deletions in the Retinoblastoma tumor suppressor gene (RB1) are frequently observed in many cancer types leading to dysregulation of the RB pathway. Here, we propose an integrative proteogenomic approach that predicts cancers with dysregulation in the RB pathway. A subset of these cancers, which we term as "RBness," lack RB1 genomic defects and yet phenocopy the transcriptional profile of RB1-defective cancers. We report RBness as a pan-cancer phenomenon, associated with patient outcome and chemotherapy response in multiple cancer types, and predictive of CDK4/6 inhibitor response in estrogen-positive breast cancer. Using RNA interference and a CRISPR-Cas9 screen in isogenic models, we find that RBness cancers also phenocopy synthetic lethal vulnerabilities of cells with RB1 genomic defects. In summary, our findings suggest that dysregulation of the RB pathway in cancers lacking RB1 genomic defects provides a molecular rationale for how these cancers could be treated.

Tumour hypoxia in driving genomic instability and tumour evolution

Intratumour hypoxia is a feature of all heterogenous solid tumours. Increased levels or subregions of tumour hypoxia are associated with an adverse clinical prognosis, particularly when this co-occurs with genomic instability. Experimental evidence points to the acquisition of DNA and chromosomal alterations in proliferating hypoxic cells secondary to inhibition of DNA repair pathways such as homologous recombination, base excision repair and mismatch repair. Cell adaptation and selection in repair-deficient cells give rise to a model whereby novel single-nucleotide mutations, structural variants and copy number alterations coexist with altered mitotic control to drive chromosomal instability and aneuploidy. Whole-genome sequencing studies support the concept that hypoxia is a critical microenvironmental cofactor alongside the driver mutations in MYC, BCL2, TP53 and PTEN in determining clonal and subclonal evolution in multiple tumour types. We propose that the hypoxic tumour microenvironment selects for unstable tumour clones which survive, propagate and metastasize under reduced immune surveillance. These aggressive features of hypoxic tumour cells underpin resistance to local and systemic therapies and unfavourable outcomes for patients with cancer. Possible ways to counter the effects of hypoxia to block tumour evolution and improve treatment outcomes are described.

One-step diagnosis of infection and lung cancer using metagenomic sequencing

BACKGROUND

Traditional detection methods face challenges in meeting the diverse clinical needs for diagnosing both lung cancer and infections within a single test. Onco-mNGS has emerged as a promising solution capable of accurately identifying infectious pathogens and tumors simultaneously. However, critical evidence is still lacking regarding its diagnostic performance in distinguishing between pulmonary infections, tumors, and non-infectious, non-tumor conditions in real clinical settings.

METHODS

In this study, data were gathered from 223 participants presenting symptoms of lung infection or tumor who underwent Onco-mNGS testing. Patients were categorized into four groups based on clinical diagnoses: infection, tumor, tumor with infection, and non-infection-non-tumor. Comparisons were made across different groups, subtypes, and stages of lung cancer regarding copy number variation (CNV) patterns, microbiome compositions, and clinical detection indices.

RESULTS

Compared to conventional infection testing methods, Onco-mNGS demonstrates superior infection detection performance, boasting a sensitivity of 81.82%, specificity of 72.55%, and an overall accuracy of 77.58%. In lung cancer diagnosis, Onco-mNGS showcases excellent diagnostic capabilities with sensitivity, specificity, accuracy, positive predictive value, and negative predictive value reaching 88.46%, 100%, 91.41%, 100%, and 90.98%, respectively. In bronchoalveolar lavage fluid (BALF) samples, these values stand at 87.5%, 100%, 94.74%, 100%, and 91.67%, respectively. Notably, more abundant CNV mutation types and higher mutation rates were observed in adenocarcinoma (ADC) compared to squamous cell carcinoma (SCC). Concurrently, onco-mNGS data revealed specific enrichment of Capnocytophaga sputigeria in the ADC group and Candida parapsilosis in the SCC group. These species exhibited significant correlations with C reaction protein (CRP) and CA153 values. Furthermore, Haemophilus influenzae was enriched in the early-stage SCC group and significantly associated with CRP values.

CONCLUSIONS

Onco-mNGS has exhibited exceptional efficiencies in the detection and differentiation of infection and lung cancer. This study provides a novel technological option for achieving single-step precise and swift detection of lung cancer.

EHMT2-mediated R-loop formation promotes the malignant progression of prostate cancer via activating Aurora B

BACKGROUND

Chromosomal instability (CIN), a hallmark of cancer, is commonly linked to poor prognosis in high-grade prostate cancer (PCa). Paradoxically, excessively high levels of CIN may impair cancer cell viability. Consequently, understanding how tumours adapt to CIN is critical for identifying novel therapeutic targets.

METHODS

Bioinformatic analyses were conducted to identify genes overexpressed in PCa tissues using The Cancer Genome Atlas (TCGA) and GEO datasets. Western blotting and immunohistochemistry assays were applied to determine the expression levels of euchromatic histone lysine methyltransferase 2 (EHMT2), pT232-Aurora B and Cullin 3 (CUL3). The proliferation of cells was measured through CCK-8 tests, clonogenesis and subcutaneous xenografts of human PCa cells in BALB/c nude mice. Live cell imaging, immunofluorescence (IF) and flow cytometry were used to confirm the role of EHMT2 in PCa cell mitosis. Co-immunoprecipitation, Western blotting and IF assays further elucidated the underlying molecular mechanisms.

RESULTS

EHMT2 was highly expressed in metastatic PCa tissues exhibiting elevated CIN and was strongly associated with adverse clinical outcomes in patients with PCa. Silencing EHMT2 impaired cell division, inducing G2/M-phase arrest and mitotic catastrophe in PCa cells. Mechanistically, EHMT2 is indispensable to ensure the full activation of Aurora B through centromeric R-loop-driven ATR-CHK1 pathway, with EHMT2 protein expression peaking during the G2/M-phase. Moreover, CUL3 was identified as a binding partner of EHMT2, mediating its polyubiquitination and destabilising its protein levels.

CONCLUSIONS

This study reveals a CUL3-EHMT2-Aurora B regulatory axis that safeguards accurate chromosome segregation in PCa cells, supporting the potential therapeutic application of EHMT2 inhibitors.

KEY POINTS

Euchromatic histone lysine methyltransferase 2 (EHMT2) is overexpressed in advanced prostate cancer, restraining catastrophic chromosomal instability (CIN) and enhancing cell fitness. EHMT2 functions via the centromeric R-loop-driven ATR-CHK1-Aurora B pathway to promote chromosomal stability. EHMT2 confers enzalutamide resistance via activating Aurora B. Cullin 3 (CUL3) promotes EHMT2 destabilisation via deubiquitination.

Gestational trophoblastic disease: understanding the molecular mechanisms of placental tumours

Gestational trophoblastic disease (GTD) describes a group of rare benign and cancerous lesions originating from the trophoblast cells of the placenta. These neoplasms are unconventional entities, being one of the few instances in which cancer develops from the cells of another organism, the foetus. Although this condition was first described over 100 years ago, the specific genetic and non-genetic drivers of this disease remain unknown to this day. However, recent findings have provided valuable insights into the potential mechanisms underlying this rare condition. Unlike previous reviews focused primarily on the clinical and diagnostic aspects of disease development, this Review consolidates the latest research concerning the role of genetics, epigenetics and microRNAs in the initiation and progression of GTD. By examining GTD from a molecular perspective, this Review provides a unique framework for understanding the pathogenesis and progression of this rare disease.

Applications of Nanopore sequencing in precision cancer medicine

Oxford Nanopore Technologies sequencing, also referred to as Nanopore sequencing, stands at the forefront of a revolution in clinical genetics, offering the potential for rapid, long read, and real-time DNA and RNA sequencing. This technology is currently making sequencing more accessible and affordable. In this comprehensive review, we explore its potential regarding precision cancer diagnostics and treatment. We encompass a critical analysis of clinical cases where Nanopore sequencing was successfully applied to identify point mutations, splice variants, gene fusions, epigenetic modifications, non-coding RNAs, and other pivotal biomarkers that defined subsequent treatment strategies. Additionally, we address the challenges of clinical applications of Nanopore sequencing and discuss the current efforts to overcome them.

DAB2IP loss in luminal a breast cancer leads to NF-κB-associated aggressive oncogenic phenotypes

Despite proven therapy options for estrogen receptor-positive (ER+) breast tumors, a substantial number of patients with ER+ breast cancer exhibit relapse with associated metastasis. Loss of expression of RasGAPs leads to poor outcomes in several cancers, including breast cancer. Mining the The Cancer Genome Atlas (TCGA) breast cancer RNA-Seq dataset revealed that low expression of the RasGAP DAB2IP was associated with a significant decrease in relapse-free survival in patients with Luminal A breast cancer. Immunostaining demonstrated that DAB2IP loss occurred in grade 2 tumors and higher. Consistent with this, genes upregulated in DAB2IP-low Luminal A tumors were shared with more aggressive tumor subtypes and were associated with proliferation, metastasis, and altered ER signaling. Low DAB2IP expression in ER+ breast cancer cells was associated with increased proliferation, enhanced stemness phenotypes, and activation of IKK, the upstream regulator of the transcription factor NF-κB. Integrating cell-based ChIP-Seq with motif analysis and TCGA RNA-Seq data, we identified a set of candidate NF-κB target genes upregulated with loss of DAB2IP linked with several oncogenic phenotypes, including altered RNA processing. This study provides insight into mechanisms associated with aggressiveness and recurrence within a subset of the typically less aggressive Luminal A breast cancer intrinsic subtype.

Prognostic Relevance of Copy Number Losses in Ovarian Cancer

BACKGROUND/OBJECTIVES

Aneuploidy is a prevalent cancer feature that occurs in many solid tumors. For example, high-grade serous ovarian cancer shows a high level of copy number alterations and genomic rearrangements. This makes genomic variants appealing as diagnostic or prognostic biomarkers, as well as for their easy detection. In this study, we focused on copy number (CN) losses shared by ovarian cancer stem cells (CSCs) to identify chromosomal regions that may be important for CSC features and, in turn, for patients' prognosis.

METHODS

Array-CGH and bioinformatic analyses on three CSCs subpopulations were performed.

RESULTS

Pathway and gene ontology analyses on genes involved in copy number loss in all CSCs revealed a significant decrease in mRNA surveillance pathway, as well as miRNA-mediated gene silencing. Then, starting from these CN losses, we validated their potential prognostic relevance by analyzing the TCGA cohort. Notably, losses of 4q34.3-q35.2, 8p21.2-p21.1, and 18q12.2-q23 were linked to increased genomic instability. Loss of 18q12.2-q23 was also related to a higher tumor stage and poor prognosis. Finally, specific genes mapping in these regions, such as PPP2R2A and TPGS2A, emerged as potential biomarkers.

CONCLUSIONS

Our findings highlight the importance of genomic alterations in ovarian cancer and their impact on tumor progression and patients' prognosis, offering advance in understanding of the application of numerical aberrations as prognostic ovarian cancer biomarkers.

AI-Powered cellular morphometric biomarkers discovered in needle biopsy of prostatic cancer predict neoadjuvant androgen deprivation therapy response and prognosis: an international multicenter retrospective study

It is imperative to identify patients with prostate cancer (PCa) who will benefit from androgen receptor signaling inhibitors that can impact quality of life upon prolonged use. Using our extensively-validated artificial-intelligence technique: cellular morphometric biomarker via machine learning (CMB-ML), we identified 13 CMBs from whole slide images of needle biopsies from the trial specimens ( NCT02430480 , n=37) that accurately predicted response to neoadjuvant androgen deprivation therapy (NADT) (AUC: 0.980). Notably, 13-CMB model stratified PCa patients into responder and non-responder groups after NADT treatment in an independent hospital cohort (n=122) that significantly associated with pathologic complete response (p=0.0005), biochemical-recurrence-free survival (p=0.024) and mTOR signaling pathway (p=0.03), suggesting potentially more clinical benefit from mTOR inhibitors in non-responder group. Additionally, genetic and genomic analysis revealed interplay between genetic variants and CMBs on NADT resistance, and provided molecular annotations for CMBs. Overall, prospective clinical implementation of 13-CMB model could assist precision care of PCa patients.

Significance

We describe a highly accurate CMB model to predict the therapeutic benefit in prostate cancer patients and uncover the complex interplay between genetic variants and CMBs on NADT resistance. Our model relies only on widely available needle biopsy specimens and provides a robust and cost-effective solution for clinical implementation.

Early Diagnostic Markers for Esophageal Squamous Cell Carcinoma: Copy Number Alteration Gene Identification and cfDNA Detection

The high mortality rate of esophageal squamous cell carcinoma (ESCC) is exacerbated by the absence of early diagnostic markers. The pronounced heterogeneity of mutations in ESCC renders copy number alterations (CNAs) more prevalent among patients. The identification of CNA genes within esophageal squamous dysplasia (ESD), a precancerous stage of ESCC, is crucial for advancing early detection efforts. Utilization of liquid biopsies via droplet-based digital PCR (ddPCR) offers a novel strategy for detecting incipient tumor traces. This study undertook a thorough investigation of CNA profiles across ESCC development stages, integrating data from existing databases and prior investigations to pinpoint and confirm CNA markers conducive to early detection of ESCC. Targeted sequencing was employed to select potential early detection genes, followed by the establishment of prediction models for ESCC early detection using ddPCR. Our analysis revealed widespread CNAs during the ESD stage, mirroring the CNA landscape observed in ESCC. A total of 40 CNA genes were identified as highly frequent in both ESCC and ESD lesions, through a comprehensive gene-level CNA analysis encompassing ESD and ESCC tissues, ESCC cell lines, and pan-cancer data sets. Subsequent validation of 5 candidate markers via ddPCR underscored the efficacy of combined predictive models encompassing PIK3CA, SOX2, EGFR, MYC, and CCND1 in early ESCC screening, as evidenced by the area-under-the-curve values exceeding 0.92 (P < .0001) across various detection contexts. The findings highlighted the significant utility of CNA genes in the early screening of ESCC, presenting robust models that could facilitate early detection, broad-scale population screening, and adjunctive diagnosis.

Contemporary Update on Clinical and Experimental Prostate Cancer Biomarkers: A Multi-Omics-Focused Approach to Detection and Risk Stratification

Prostate cancer remains a significant health challenge, being the most prevalent non-cutaneous cancer in men worldwide. This review discusses the critical advancements in biomarker discovery using single-omics and multi-omics approaches. Multi-omics, integrating genomic, transcriptomic, proteomic, metabolomic, and epigenomic data, offers a comprehensive understanding of the molecular heterogeneity of prostate cancer, leading to the identification of novel biomarkers and therapeutic targets. This holistic approach not only enhances the specificity and sensitivity of prostate cancer detection but also supports the development of personalized treatment strategies. Key studies highlighted include the identification of novel genes, genetic mutations, peptides, metabolites, and potential biomarkers through multi-omics analyses, which have shown promise in improving prostate cancer management. The integration of multi-omics in clinical practice can potentially revolutionize prostate cancer prognosis and treatment, paving the way for precision medicine. This review underscores the importance of continued research and the application of multi-omics to overcome current challenges in prostate cancer diagnosis and therapy.

An elevated rate of whole-genome duplications in cancers from Black patients

In the United States, Black individuals have higher rates of cancer mortality than any other racial group. Here, we examine chromosome copy number changes in cancers from more than 1800 self-reported Black patients. We find that tumors from self-reported Black patients are significantly more likely to exhibit whole-genome duplications (WGDs), a genomic event that enhances metastasis and aggressive disease, compared to tumors from self-reported white patients. This increase in WGD frequency is observed across multiple cancer types, including breast, endometrial, and lung cancer, and is associated with shorter patient survival. We further demonstrate that combustion byproducts are capable of inducing WGDs in cell culture, and cancers from self-reported Black patients exhibit mutational signatures consistent with exposure to these carcinogens. In total, these findings identify a type of genomic alteration that is associated with environmental exposures and that may influence racial disparities in cancer outcomes.

Insights into the Clinical, Biological and Therapeutic Impact of Copy Number Alteration in Cancer

Copy number alterations (CNAs), resulting from the gain or loss of genetic material from as little as 50 base pairs or as big as entire chromosome(s), have been associated with many congenital diseases, de novo syndromes and cancer. It is established that CNAs disturb the dosage of genomic regions including enhancers/promoters, long non-coding RNA and gene(s) among others, ultimately leading to an altered balance of key cellular functions. In cancer, CNAs have been associated with almost all steps of the disease: predisposition, initiation, development, maintenance, response to treatment, resistance, and relapse. Therefore, understanding how specific CNAs contribute to tumourigenesis may provide prognostic insight and ultimately lead to the development of new therapeutic approaches to improve patient outcomes. In this review, we provide a snapshot of what is currently known about CNAs and cancer, incorporating topics regarding their detection, clinical impact, origin, and nature, and discuss the integration of innovative genetic engineering strategies, to highlight the potential for targeting CNAs using novel, dosage-sensitive and less toxic therapies for CNA-driven cancer.

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.

Molecular and Clinical Determinants of Acquired Resistance and Treatment Duration for Targeted Therapies in Colorectal Cancer

PURPOSE

Targeted therapies have improved outcomes for patients with metastatic colorectal cancer, but their impact is limited by rapid emergence of resistance. We hypothesized that an understanding of the underlying genetic mechanisms and intrinsic tumor features that mediate resistance to therapy will guide new therapeutic strategies and ultimately allow the prevention of resistance.

EXPERIMENTAL DESIGN

We assembled a series of 52 patients with paired pretreatment and progression samples who received therapy targeting EGFR (n = 17), BRAF V600E (n = 17), KRAS G12C (n = 15), or amplified HER2 (n = 3) to identify molecular and clinical factors associated with time on treatment (TOT).

RESULTS

All patients stopped treatment for progression and TOT did not vary by oncogenic driver (P = 0.5). Baseline disease burden (≥3 vs. <3 sites, P = 0.02), the presence of hepatic metastases (P = 0.02), and gene amplification on baseline tissue (P = 0.03) were each associated with shorter TOT. We found evidence of chromosomal instability (CIN) at progression in patients with baseline MAPK pathway amplifications and those with acquired gene amplifications. At resistance, copy-number changes (P = 0.008) and high number (≥5) of acquired alterations (P = 0.04) were associated with shorter TOT. Patients with hepatic metastases demonstrated both higher number of emergent alterations at resistance and enrichment of mutations involving receptor tyrosine kinases.

CONCLUSIONS

Our genomic analysis suggests that high baseline CIN or effective induction of enhanced mutagenesis on targeted therapy underlies rapid progression. Longer response appears to result from a progressive acquisition of genomic or chromosomal instability in the underlying cancer or from the chance event of a new resistance alteration.

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

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

The yin and yang of chromosomal instability in prostate cancer

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

Performance of a novel spectroscopy-based tool for adjuvant therapy decision-making in hormone receptor-positive breast cancer: a validation study

PURPOSE

Digistain Index (DI), measured using an inexpensive mid-infrared spectrometer, reflects the level of aneuploidy in unstained tissue sections and correlates with tumor grade. We investigated whether incorporating DI with other clinicopathological variables could predict outcomes in patients with early breast cancer.

METHODS

DI was calculated in 801 patients with hormone receptor-positive, HER2-negative primary breast cancer and ≤ 3 positive lymph nodes. All patients were treated with systemic endocrine therapy and no chemotherapy. Multivariable proportional hazards modeling was used to incorporate DI with clinicopathological variables to generate the Digistain Prognostic Score (DPS). DPS was assessed for prediction of 5- and 10-year outcomes (recurrence, recurrence-free survival [RFS] and overall survival [OS]) using receiver operating characteristics and Cox proportional hazards regression models. Kaplan-Meier analysis evaluated the ability of DPS to stratify risk.

RESULTS

DPS was consistently highly accurate and had negative predictive values for all three outcomes, ranging from 0.96 to 0.99 at 5 years and 0.84 to 0.95 at 10 years. DPS demonstrated statistically significant prognostic ability with significant hazard ratios (95% CI) for low- versus high-risk classification for RFS, recurrence and OS (1.80 [CI 1.31-2.48], 1.83 [1.32-2.52] and 1.77 [1.28-2.43], respectively; all P < 0.001).

CONCLUSION

DPS showed high accuracy and predictive performance, was able to stratify patients into low or high-risk, and considering its cost and rapidity, has the potential to offer clinical utility.

Evolving copy number gains promote tumor expansion and bolster mutational diversification

The timing and fitness effect of somatic copy number alterations (SCNA) in cancer evolution remains poorly understood. Here we present a framework to determine the timing of a clonal SCNA that encompasses multiple gains. This involves calculating the proportion of time from its last gain to the onset of population expansion (lead time) as well as the proportion of time prior to its first gain (initiation time). Our method capitalizes on the observation that a genomic segment, while in a specific copy number (CN) state, accumulates point mutations proportionally to its CN. Analyzing 184 whole genome sequenced samples from 75 patients across five tumor types, we commonly observe late gains following early initiating events, occurring just before the clonal expansion relevant to the sampling. These include gains acquired after genome doubling in more than 60% of cases. Notably, mathematical modeling suggests that late clonal gains may contain final-expansion drivers. Lastly, SCNAs bolster mutational diversification between subpopulations, exacerbating the circle of proliferation and increasing heterogeneity.

Multi-omics approach for identifying CNV-associated lncRNA signatures with prognostic value in prostate cancer

BACKGROUND

Prostate cancer, the second most prevalent malignancy among men, poses a significant threat to affected patients' well-being due to its poor prognosis. Novel biomarkers are required to enhance clinical outcomes and tailor personalized treatments. Herein, we describe our research to explore the prognostic value of long non-coding RNAs (lncRNAs) deregulated by copy number variations (CNVs) in prostate cancer.

METHODS

The study employed an integrative multi-omics data analysis of the prostate cancer transcriptomic, CNV and methylation datasets to identify prognosis-related subtypes. Subtype-specific expression profiles of protein-coding genes (PCGs) and lncRNAs were determined. We analysed CNV patterns of lncRNAs across the genome to identify subtype-specific lncRNAs with CNV changes. LncRNAs exhibiting significant amplification or deletion and a positive correlation were designated CNV-deregulated lncRNAs. A prognostic risk score model was subsequently developed using these CNV-driven lncRNAs.

RESULTS

Six molecular subtypes of prostate cancer were identified, demonstrating significant differences in prognosis (P = 0.034). The CNV profiles of subtype-specific lncRNAs were examined, revealing their correlation with CNV amplification or deletion. Six lncRNAs (CCAT2, LINC01593, LINC00276, GACAT2, LINC00457, LINC01343) were selected based on significant CNV amplifications or deletions using a rigorous univariate Cox proportional risk regression model. A robust risk score model was developed, stratifying patients into high-risk and low-risk categories. Notably, our prognostic model based on these six lncRNAs exhibited exceptional predictive capabilities for recurrence-free survival (RFS) in prostate cancer patients (P = 0.024).

CONCLUSIONS

Our study successfully identified a prognostic risk score model comprising six CNV-driven lncRNAs that could potentially be prognostic biomarkers for prostate cancer. These lncRNA signatures are closely associated with RFS, providing promising prospects for improved patient prognostication and personalized therapeutic strategies for novel prostate cancer treatment.

Targeting chromosomal instability and aneuploidy in cancer

Cancer development and therapy resistance are driven by chromosomal instability (CIN), which causes chromosome gains and losses (i.e., aneuploidy) and structural chromosomal alterations. Technical limitations and knowledge gaps have delayed therapeutic targeting of CIN and aneuploidy in cancers. However, our toolbox for creating and studying aneuploidy in cell models has greatly expanded recently. Moreover, accumulating evidence suggests that seven conventional antimitotic chemotherapeutic drugs achieve clinical response by inducing CIN instead of mitotic arrest, although additional anticancer activities may also contribute in vivo. In this review, we discuss these recent developments. We also highlight new discoveries, which together show that 25 chromosome arm aneuploidies (CAAs) may be targetable by 36 drugs across 14 types of cancer. Collectively, these advances offer many new opportunities to improve cancer treatment.

Aneuploid embryonic stem cells drive teratoma metastasis

Aneuploidy, a deviation of the chromosome number from euploidy, is one of the hallmarks of cancer. High levels of aneuploidy are generally correlated with metastasis and poor prognosis in cancer patients. However, the causality of aneuploidy in cancer metastasis remains to be explored. Here we demonstrate that teratomas derived from aneuploid murine embryonic stem cells (ESCs), but not from isogenic diploid ESCs, disseminated to multiple organs, for which no additional copy number variations were required. Notably, no cancer driver gene mutations were identified in any metastases. Aneuploid circulating teratoma cells were successfully isolated from peripheral blood and showed high capacities for migration and organ colonization. Single-cell RNA sequencing of aneuploid primary teratomas and metastases identified a unique cell population with high stemness that was absent in diploid ESCs-derived teratomas. Further investigation revealed that aneuploid cells displayed decreased proteasome activity and overactivated endoplasmic reticulum (ER) stress during differentiation, thereby restricting the degradation of proteins produced from extra chromosomes in the ESC state and causing differentiation deficiencies. Noticeably, both proteasome activator Oleuropein and ER stress inhibitor 4-PBA can effectively inhibit aneuploid teratoma metastasis.

Acquired copy number variation in prostate tumours: a review of common somatic copy number alterations, how they are formed and their clinical utility

Prostate cancer is one of the most commonly diagnosed cancers in men and unfortunately, disease will progress in up to a third of patients despite primary treatment. Currently, there is a significant lack of prognostic tests that accurately predict disease course; however, the acquisition of somatic chromosomal variation in the form of DNA copy number variants may help understand disease progression. Notably, studies have found that a higher burden of somatic copy number alterations (SCNA) correlates with more aggressive disease, recurrence after surgery and metastasis. Here we will review the literature surrounding SCNA formation, including the roles of key tumour suppressors and oncogenes (PTEN, BRCA2, NKX3.1, ERG and AR), and their potential to inform diagnostic and prognostic clinical testing to improve predictive value. Ultimately, SCNAs, or inherited germline alterations that predispose to SCNAs, could have significant clinical utility in diagnostic and prognostic tests, in addition to guiding therapeutic selection.

A comprehensive analysis of clinical and polygenic germline influences on somatic mutational burden

Tumor mutational burden (TMB), the total number of somatic mutations in the tumor, and copy number burden (CNB), the corresponding measure of aneuploidy, are established fundamental somatic features and emerging biomarkers for immunotherapy. However, the genetic and non-genetic influences on TMB/CNB and, critically, the manner by which they influence patient outcomes remain poorly understood. Here, we present a large germline-somatic study of TMB/CNB with >23,000 individuals across 17 cancer types, of which 12,000 also have extensive clinical, treatment, and overall survival (OS) measurements available. We report dozens of clinical associations with TMB/CNB, observing older age and male sex to have a strong effect on TMB and weaker impact on CNB. We additionally identified significant germline influences on TMB/CNB, including fine-scale European ancestry and germline polygenic risk scores (PRSs) for smoking, tanning, white blood cell counts, and educational attainment. We quantify the causal effect of exposures on somatic mutational processes using Mendelian randomization. Many of the identified features associated with TMB/CNB were additionally associated with OS for individuals treated at a single tertiary cancer center. For individuals receiving immunotherapy, we observed a complex relationship between PRSs for educational attainment, self-reported college attainment, TMB, and survival, suggesting that the influence of this biomarker may be substantially modified by socioeconomic status. While the accumulation of somatic alterations is a stochastic process, our work demonstrates that it can be shaped by host characteristics including germline genetics.

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.

Completing a genomic characterisation of microscopic tumour samples with copy number

BACKGROUND

Genomic insights in settings where tumour sample sizes are limited to just hundreds or even tens of cells hold great clinical potential, but also present significant technical challenges. We previously developed the DigiPico sequencing platform to accurately identify somatic mutations from such samples.

RESULTS

Here, we complete this genomic characterisation with copy number. We present a novel protocol, PicoCNV, to call allele-specific somatic copy number alterations from picogram quantities of tumour DNA. We find that PicoCNV provides exactly accurate copy number in 84% of the genome for even the smallest samples, and demonstrate its clinical potential in maintenance therapy.

CONCLUSIONS

PicoCNV complements our existing platform, allowing for accurate and comprehensive genomic characterisations of cancers in settings where only microscopic samples are available.

A pan-cancer landscape of pathogenic somatic copy number variations

OBJECTIVE

Copy number variations (CNVs) play crucial roles in physiological and pathological processes, including cancer. However, the functional implications of somatic CNVs in tumor progression and evolution remain unclear. This study focuses on identifying CNV alterations with high pathogenic potential that drive and sustain tumorigenesis, distinguishing them from passenger alterations that accumulate during tumor growth. Our goal is to explore the variability of CNVs across different tumor types and infer their impact on tumor cell functions.

METHODS

Starting from 7352 copy number profiles across 33 different cancer types, we infer the pathogenicity of each CNV and perform both intra- and inter-tumor analyses to predict the functional impact of different genomic patterns. We evaluate the actionability of genes belonging to altered regions and we correlate the presence of pathogenic regions with genome instability patterns and patients' survival.

RESULTS

Our analysis uncovered large heterogeneity among different tumors suggesting in many cases distinct genetic drivers of tumorigenesis. Recurrent genomic alterations frequently coincide with dysfunctional homologous recombination pathways and negative regulation of the immune system. In certain tumors, the number of pathogenic CNVs emerged as a prognostic biomarker, highlighting their significance in cancer progression.

CONCLUSION

This study contributes to elucidate the functional impact of pathogenic CNVs in tumor progression and sheds light on their potential as prognostic markers in specific cancer types.

Classification of HER2-negative breast cancers by ERBB2 copy number alteration status reveals molecular differences associated with chromosome 17 gene aberrations

Background

Recently, HER2-negative breast cancers have been reclassified by protein expression into 'HER2-low' and 'HER2-zero' subgroups, but the consideration of HER2-low breast cancer as a distinct biological subtype with differing prognoses remains controversial. By contrast, non-neutral ERBB2 copy number alteration (CNA) status is associated with inferior survival outcomes compared to ERBB2 CNA-neutral breast cancer, providing an alternative approach to classification.

Methods

Here, we investigated the molecular landscape of non-metastatic HER2-negative BCs in relation to ERBB2 CNA status to elucidate biological differences. Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas (TCGA) TCGA-BRCA datasets (n = 1875) were analyzed.

Results

Nearly two-fifths of the cohort harbored ERBB2 CNAs (39.4%), which were significantly enriched within hormone receptor-negative (56.1%) than within hormone receptor-positive BCs (35.5%; p < 0.0001). Globally, CNAs across the genome were significantly higher in ERBB2 non-neutral compared to neutral cohorts (p < 0.0001). Notably, genetic aberrations on chromosome 17 - BRCA1, NF1, TP53, MAP2K4, and NCOR1 - were widespread in the ERBB2 non-neutral cases. While chromosome 17q arm-level alterations were largely in tandem with ERBB2 CNA status, arm-level loss in chromosome 17p was prevalent regardless of ERBB2 gain, amplification, or loss. Differential gene expression analysis demonstrated that pathways involved in the cell cycle, proteasome, and DNA replication were upregulated in ERBB2 non-neutral cases.

Conclusion

Classification of HER2-negative BCs according to ERBB2 CNA status reveals differences in the genomic landscape. The implications of concurrent aberrations in other genes on chromosome 17 merit further research in ERBB2 non-neutral BCs.

Neuroblastoma Patients' Outcome and Chromosomal Instability

Chromosomal instability (CIN) induces a high rate of losses or gains of whole chromosomes or parts of chromosomes. It is a hallmark of most human cancers and one of the causes of aneuploidy and intra-tumor heterogeneity. The present study aimed to evaluate the potential prognostic role of CIN in NB patients at diagnosis. We performed array comparative genomic hybridization analyses on 451 primary NB patients at the onset of the disease. To assess global chromosomal instability with high precision, we focused on the total number of DNA breakpoints of gains or losses of chromosome arms. For each tumor, an array-CGH-based breakpoint instability index (BPI) was assigned which defined the total number of chromosomal breakpoints per genome. This approach allowed us to quantify CIN related to whole genome disruption in all NB cases analyzed. We found differences in chromosomal breakages among the NB clinical risk groups. High BPI values are negatively associated with survival of NB patients. This association remains significant when correcting for stage, age, and MYCN status in the Cox model. Stratified analysis confirms the prognostic effect of BPI index in low-risk NB patients with non-amplified MYCN and with segmental chromosome aberrations.

Analysis of genetic biomarkers, polymorphisms in ADME-related genes and their impact on pharmacotherapy for prostate cancer

Prostate cancer (PCa) is a non-cutaneous malignancy in males with wide variation in incidence rates across the globe. It is the second most reported cause of cancer death. Its etiology may have been linked to genetic polymorphisms, which are not only dominating cause of malignancy casualties but also exerts significant effects on pharmacotherapy outcomes. Although many therapeutic options are available, but suitable candidates identified by useful biomarkers can exhibit maximum therapeutic efficacy. The single-nucleotide polymorphisms (SNPs) reported in androgen receptor signaling genes influence the effectiveness of androgen receptor pathway inhibitors and androgen deprivation therapy. Furthermore, SNPs located in genes involved in transport, drug metabolism, and efflux pumps also influence the efficacy of pharmacotherapy. Hence, SNPs biomarkers provide the basis for individualized pharmacotherapy. The pharmacotherapeutic options for PCa include hormonal therapy, chemotherapy (Docetaxel, Mitoxantrone, Cabazitaxel, and Estramustine, etc.), and radiotherapy. Here, we overview the impact of SNPs reported in various genes on the pharmacotherapy for PCa and evaluate current genetic biomarkers with an emphasis on early diagnosis and individualized treatment strategy in PCa.

Refphase: Multi-sample phasing reveals haplotype-specific copy number heterogeneity

Most computational methods that infer somatic copy number alterations (SCNAs) from bulk sequencing of DNA analyse tumour samples individually. However, the sequencing of multiple tumour samples from a patient's disease is an increasingly common practice. We introduce Refphase, an algorithm that leverages this multi-sampling approach to infer haplotype-specific copy numbers through multi-sample phasing. We demonstrate Refphase's ability to infer haplotype-specific SCNAs and characterise their intra-tumour heterogeneity, to uncover previously undetected allelic imbalance in low purity samples, and to identify parallel evolution in the context of whole genome doubling in a pan-cancer cohort of 336 samples from 99 tumours.

Distinct aneuploid evolution of astrocytoma and glioblastoma during recurrence

Astrocytoma and glioblastoma (GB) are reclassified subtypes of adult diffuse gliomas based on distinct isocitrate dehydrogenase (IDH) mutation in the fifth edition of the WHO Classification of Tumors of the Central Nervous System. The recurrence of gliomas is a common and inevitable challenge, and analyzing the distinct genomic alterations in astrocytoma and GB could provide insights into their progression. This study conducted a longitudinal investigation, utilizing whole-exome sequencing, on 65 paired primary/recurrent gliomas. It examined chromosome arm aneuploidies, copy number variations (CNVs) of cancer-related genes and pathway enrichments during the relapse. The veracity of these findings was verified through the integration of our data with multiple public resources and by corroborative immunohistochemistry (IHC). The results revealed a greater prevalence of aneuploidy changes and acquired CNVs in recurrent lower grade astrocytoma than in relapsed grade 4 astrocytoma and GB. Larger aneuploidy changes were predictive of an unfavorable prognosis in lower grade astrocytoma (P < 0.05). Further, patients with acquired gains of 1q, 6p or loss of 13q at recurrence had a shorter overall survival in lower grade astrocytoma (P < 0.05); however, these prognostic effects were confined in grade 4 astrocytoma and GB. Moreover, acquired gains of 12 genes (including VEGFA) on 6p during relapse were associated with unfavorable prognosis for lower grade astrocytoma patients. Notably, elevated VEGFA expression during recurrence corresponded to poorer survival, validated through IHC and CGGA data. To summarize, these findings offer valuable insights into the progression of gliomas and have implications for guiding therapeutic approaches during recurrence.

Disentangling the roles of aneuploidy, chromosomal instability and tumour heterogeneity in developing resistance to cancer therapies

Aneuploidy is defined as the cellular state of having a number of chromosomes that deviates from a multiple of the normal haploid chromosome number of a given organism. Aneuploidy can be present in a static state: Down syndrome individuals stably maintain an extra copy of chromosome 21 in their cells. In cancer cells, however, aneuploidy is usually present in combination with chromosomal instability (CIN) which leads to a continual generation of new chromosomal alterations and the development of intratumour heterogeneity (ITH). The prevalence of cells with specific chromosomal alterations is further shaped by evolutionary selection, for example, during the administration of cancer therapies. Aneuploidy, CIN and ITH have each been individually associated with poor prognosis in cancer, and a wealth of evidence suggests they contribute, either alone or in combination, to cancer therapy resistance by providing a reservoir of potential resistant states, or the ability to rapidly evolve resistance. A full understanding of the contribution and interplay between aneuploidy, CIN and ITH is required to tackle therapy resistance in cancer patients. However, these characteristics often co-occur and are intrinsically linked, presenting a major challenge to defining their individual contributions. Moreover, their accurate measurement in both experimental and clinical settings is a technical hurdle. Here, we attempt to deconstruct the contribution of the individual and combined roles of aneuploidy, CIN and ITH to therapy resistance in cancer, and outline emerging approaches to measure and disentangle their roles as a step towards integrating these principles into cancer therapeutic strategy.

Dimension reduction for integrative survival analysis

We propose a constrained maximum partial likelihood estimator for dimension reduction in integrative (e.g., pan-cancer) survival analysis with high-dimensional predictors. We assume that for each population in the study, the hazard function follows a distinct Cox proportional hazards model. To borrow information across populations, we assume that each of the hazard functions depend only on a small number of linear combinations of the predictors (i.e., "factors"). We estimate these linear combinations using an algorithm based on "distance-to-set" penalties. This allows us to impose both low-rankness and sparsity on the regression coefficient matrix estimator. We derive asymptotic results that reveal that our estimator is more efficient than fitting a separate proportional hazards model for each population. Numerical experiments suggest that our method outperforms competitors under various data generating models. We use our method to perform a pan-cancer survival analysis relating protein expression to survival across 18 distinct cancer types. Our approach identifies six linear combinations, depending on only 20 proteins, which explain survival across the cancer types. Finally, to validate our fitted model, we show that our estimated factors can lead to better prediction than competitors on four external datasets.

Low-coverage and cost-effective whole-genome sequencing assay for glioma risk stratification

PURPOSE

To investigate chromosomal instability (CIN) as a biomarker for glioma risk stratifications, with cost-effective, low-coverage whole-genome sequencing assay (WGS).

METHODS

Thirty-five formalin-fixed paraffin-embedded glioma samples were collected from Huashan Hospital. DNA was sent for WGS by Illumina X10 at low (median) genome coverage of 1.86x (range: 1.03-3.17×), followed by copy number analyses, using a customized bioinformatics workflow-Ultrasensitive Copy number Aberration Detector.

RESULTS

Among the 35 glioma patients, 12 were grade IV, 10 grade III, 11 grade II, and 2 Grade I cases, with high chromosomal instability (CIN +) in 24 (68.6%) of the glioma patients. The other 11 (31.4%) had lower chromosomal instability (CIN-). CIN significantly correlates with overall survival (P = 0.00029). Patients with CIN + /7p11.2 + (12 grade IV and 3 grade III) had the worst survival ratio (hazard ratio:16.2, 95% CI:6.3-41.6) with a median overall survival of 24 months. Ten (66.7%) patients died during the first two follow-up years. In the CIN + patients without 7p11.2 + (6 grade III, 3 grade II), 3 (33.3%) patients died during follow-up, and the estimated overall survival was around 65 months. No deaths were reported in the 11 CIN- patients (2 grade I, 8 grade II, 1 grade III) during the 80-month follow-up period. In this study, chromosomal instability served as a prognosis factor for gliomas independent of tumor grades.

CONCLUSION

It is feasible to use cost-effective, low-coverage WGS for risk stratification of glioma. Elevated chromosomal instability is associated with poor prognosis.

Oncogene-like addiction to aneuploidy in human cancers

Most cancers exhibit aneuploidy, but its functional significance in tumor development is controversial. Here, we describe ReDACT (Restoring Disomy in Aneuploid cells using CRISPR Targeting), a set of chromosome engineering tools that allow us to eliminate specific aneuploidies from cancer genomes. Using ReDACT, we created a panel of isogenic cells that have or lack common aneuploidies, and we demonstrate that trisomy of chromosome 1q is required for malignant growth in cancers harboring this alteration. Mechanistically, gaining chromosome 1q increases the expression of MDM4 and suppresses p53 signaling, and we show that TP53 mutations are mutually exclusive with 1q aneuploidy in human cancers. Thus, tumor cells can be dependent on specific aneuploidies, raising the possibility that these "aneuploidy addictions" could be targeted as a therapeutic strategy.

Integrated exome sequencing and microarray analyses detected genetic defects and underlying pathways of hepatocellular carcinoma

We performed whole exome sequencing (WES) and microarray analysis to detect somatic variants and copy number alterations (CNAs) for underlying mechanisms in a case series of hepatocellular carcinoma (HCC) with paired DNA samples from tumor and adjacent nontumor tissues. Clinicopathologic findings based on Edmondson-Steiner (E-S) grading, Barcelona-Clinic Liver Cancer (BCLC) stages, recurrence, and survival status and their associations with tumor mutation burden (TMB) and CNA burden (CNAB) were evaluated. WES from 36 cases detected variants in the TP53, AXIN1, CTNNB1, and SMARCA4 genes, amplifications of the AKT3, MYC, and TERT genes, and deletions of the CDH1, TP53, IRF2, RB1, RPL5, and PTEN genes. These genetic defects affecting the p53/cell cycle control, PI3K/Ras, and β-catenin pathways were observed in approximately 80% of cases. A germline variant in the ALDH2 gene was detected in 52% of the cases. Significantly higher CNAB in patients with poor prognosis by E-S grade III, BCLC stage C, and recurrence than patients with good prognosis by grade III, stage A, grade III and nonrecurrence was noted. Further analysis on a large case series to correlate genomic profiling with clinicopathologic classifications could provide evidence for diagnostic interpretation, prognostic prediction, and target intervention on involved genes and pathways.

A harmonized resource of integrated prostate cancer clinical, -omic, and signature features

Genomic and transcriptomic data have been generated across a wide range of prostate cancer (PCa) study cohorts. These data can be used to better characterize the molecular features associated with clinical outcomes and to test hypotheses across multiple, independent patient cohorts. In addition, derived features, such as estimates of cell composition, risk scores, and androgen receptor (AR) scores, can be used to develop novel hypotheses leveraging existing multi-omic datasets. The full potential of such data is yet to be realized as independent datasets exist in different repositories, have been processed using different pipelines, and derived and clinical features are often not provided or  not standardized. Here, we present the curatedPCaData R package, a harmonized data resource representing >2900 primary tumor, >200 normal tissue, and >500 metastatic PCa samples across 19 datasets processed using standardized pipelines with updated gene annotations. We show that meta-analysis across harmonized studies has great potential for robust and clinically meaningful insights. curatedPCaData is an open and accessible community resource with code made available for reproducibility.

Interferon signaling promotes tolerance to chromosomal instability during metastatic evolution in renal cancer

Molecular routes to metastatic dissemination are critical determinants of aggressive cancers. Through in vivo CRISPR-Cas9 genome editing, we generated somatic mosaic genetically engineered models that faithfully recapitulate metastatic renal tumors. Disruption of 9p21 locus is an evolutionary driver to systemic disease through the rapid acquisition of complex karyotypes in cancer cells. Cross-species analysis revealed that recurrent patterns of copy number variations, including 21q loss and dysregulation of the interferon pathway, are major drivers of metastatic potential. In vitro and in vivo genomic engineering, leveraging loss-of-function studies, along with a model of partial trisomy of chromosome 21q, demonstrated a dosage-dependent effect of the interferon receptor genes cluster as an adaptive mechanism to deleterious chromosomal instability in metastatic progression. This work provides critical knowledge on drivers of renal cell carcinoma progression and defines the primary role of interferon signaling in constraining the propagation of aneuploid clones in cancer evolution.

Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations

Identifying patients that are likely to respond to cancer immunotherapy is an important, yet highly challenging clinical need. Using 3139 patients across 17 different cancer types, we comprehensively studied the ability of two common copy-number alteration (CNA) scores-the tumor aneuploidy score (AS) and the fraction of genome single nucleotide polymorphism encompassed by copy-number alterations (FGA)-to predict survival following immunotherapy in both pan-cancer and individual cancer types. First, we show that choice of cutoff during CNA calling significantly influences the predictive power of AS and FGA for patient survival following immunotherapy. Remarkably, by using proper cutoff during CNA calling, AS and FGA can predict pan-cancer survival following immunotherapy for both high-TMB and low-TMB patients. However, at the individual cancer level, our data suggest that the use of AS and FGA for predicting immunotherapy response is currently limited to only a few cancer types. Therefore, larger sample sizes are needed to evaluate the clinical utility of these measures for patient stratification in other cancer types. Finally, we propose a simple, non-parameterized, elbow-point-based method to help determine the cutoff used for calling CNAs.

Mutation Burden Independently Predicts Survival in the Pan-Cancer Atlas

PURPOSE

Long-standing clinical predictors of cancer survival have included histopathologic type, stage, and grade. We hypothesized that the principal categories of tumor somatic mutations might also portend survival. We investigated this hypothesis using the Pan-Cancer Atlas, encompassing clinical, genomic, and outcome data of 10,652 patients and 32 cancer types.

METHODS

We evaluated the prognostic capability of cancer type, stage, grade and the burden of each major mutation category on overall and disease-specific survival. Mutation categories included short substitution and insertion-deletion mutations (SMs), copy number alterations (CNAs), and gene fusions.

RESULTS

SM count and CNA fraction proved to be strong independent predictors of survival (joint P = 5.3e-95) that remained highly significant when adjusted for the traditional factors. Importantly, the relationship between mutation burden and survival proved to be nonlinear (P = 9.5e-56); survival improved at both low- and high-burden extremes. In clinically predictive modeling, SM count together with CNA fraction meaningfully distinguished survival even among patients sharing a given cancer type, stage, or grade.

CONCLUSION

Burden of somatic mutation is a key index of survival of analogous clinical utility to these traditional factors.

Chromosome-specific segment size alterations are determinants of prognosis in prostate cancer

Currently, risk stratification is the most difficult problem in prostate cancer (PCa) management. Gleason grading cannot adequately predict cancer progression. This study aimed to identify chromosome-specific segment size alterations that could aid risk stratification and predict metastasis using a retrospective cohort-study strategy. A binary logistic regression model was generated using 16 chromosome-specific segments with size alterations (deletions and amplifications) that showed associations with disease stage (primary versus metastatic). The regression model was trained with the MSKCC PIK3R1 PCa cohort (n = 1417), and validated with the TCGA Firehose Legacy (n = 500), MSKCC Prostate Oncogenome Project (n = 218), and the SU2C/PCF Dream Team (n = 150) PCa cohorts. Furthermore, the capacity of the model to predict metastasis between primary tumours with metastasis (n = 54) and primary tumours without metastasis (n = 54) was tested. The accuracy, sensitivity, and specificity of the model at disease stage stratification ranged from 69.02% to 88.55%, 72.8% to 86.00% and 66.30% to 89.50%, respectively. The model also showed good performance at metastasis prediction with accuracy, sensitivity, and specificity of 57.41%, 62.96% and 51.85%, respectively. The study conclusion was that chromosome-specific segment size alterations can aid risk stratification and metastasis prediction. The significance of the study findings is that in combinations with clinical, biochemical, and histopathological variables, chromosome-specific alterations could improve current risk stratification and prediction models for PCa.

Utility of CYP2D6 copy number variants as prognostic biomarker in localized anal squamous cell carcinoma

BACKGROUND

Anal squamous cell carcinoma (ASCC) is an infrequent tumor whose treatment has not changed since the 1970s. The aim of this study is the identification of biomarkers allowing personalized treatments and improvement of therapeutic outcomes.

METHODS

Forty-six paraffin tumor samples from ASCC patients were analyzed by whole-exome sequencing. Copy number variants (CNVs) were identified and their relation to disease-free survival (DFS) was studied and validated in an independent retrospective cohort of 101 ASCC patients from the Multidisciplinary Spanish Digestive Cancer Group (GEMCAD). GEMCAD cohort proteomics allowed assessing the biological features of these tumors.

RESULTS

On the discovery cohort, the median age was 61 years old, 50% were males, stages I/II/III: 3 (7%)/16 (35%)/27 (58%), respectively, median DFS was 33 months, and overall survival was 45 months. Twenty-nine genes whose duplication was related to DFS were identified. The most representative was duplications of the CYP2D locus, including CYP2D6, CYP2D7P, and CYP2D8P genes. Patients with CYP2D6 CNV had worse DFS at 5 years than those with two CYP2D6 copies (21% vs. 84%; p < .0002, hazard ratio [HR], 5.8; 95% confidence interval [CI], 2.7-24.9). In the GEMCAD validation cohort, patients with CYP2D6 CNV also had worse DFS at 5 years (56% vs. 87%; p = .02, HR = 3.6; 95% CI, 1.1-5.7). Mitochondria and mitochondrial cell-cycle proteins were overexpressed in patients with CYP2D6 CNV.

CONCLUSIONS

Tumor CYP2D6 CNV identified patients with a significantly worse DFS at 5 years among localized ASCC patients treated with 5-fluorouracil, mitomycin C, and radiotherapy. Proteomics pointed out mitochondria and mitochondrial cell-cycle genes as possible therapeutic targets for these high-risk patients.

PLAIN LANGUAGE SUMMARY

Anal squamous cell carcinoma is an infrequent tumor whose treatment has not been changed since the 1970s. However, disease-free survival in late staged tumors is between 40% and 70%. The presence of an alteration in the number of copies of CYP2D6 gene is a biomarker of worse disease-free survival. The analysis of the proteins in these high-risk patients pointed out mitochondria and mitochondrial cell-cycle genes as possible therapeutic targets. Therefore, the determination of the number of copies of CYP2D6 allows the identification of anal squamous carcinoma patients with a high-risk of relapse that could be redirected to a clinical trial. Additionally, this study may be useful to suggest new treatment strategies to increase current therapy efficacy.

Prognostic Values of Gene Copy Number Alterations in Prostate Cancer

Whilst risk prediction for individual prostate cancer (PCa) cases is of a high priority, the current risk stratification indices for PCa management have severe limitations. This study aimed to identify gene copy number alterations (CNAs) with prognostic values and to determine if any combination of gene CNAs could have risk stratification potentials. Clinical and genomic data of 500 PCa cases from the Cancer Genome Atlas stable were retrieved from the Genomic Data Commons and cBioPortal databases. The CNA statuses of a total of 52 genetic markers, including 21 novel markers and 31 previously identified potential prognostic markers, were tested for prognostic significance. The CNA statuses of a total of 51/52 genetic markers were significantly associated with advanced disease at an odds ratio threshold of ≥1.5 or ≤0.667. Moreover, a Kaplan-Meier test identified 27/52 marker CNAs which correlated with disease progression. A Cox Regression analysis showed that the amplification of MIR602 and deletions of MIR602, ZNF267, MROH1, PARP8, and HCN1 correlated with a progression-free survival independent of the disease stage and Gleason prognostic group grade. Furthermore, a binary logistic regression analysis identified twenty-two panels of markers with risk stratification potentials. The best model of 7/52 genetic CNAs, which included the SPOP alteration, SPP1 alteration, CCND1 amplification, PTEN deletion, CDKN1B deletion, PARP8 deletion, and NKX3.1 deletion, stratified the PCa cases into a localised and advanced disease with an accuracy of 70.0%, sensitivity of 85.4%, specificity of 44.9%, positive predictive value of 71.67%, and negative predictive value of 65.35%. This study validated prognostic gene level CNAs identified in previous studies, as well as identified new genetic markers with CNAs that could potentially impact risk stratification in PCa.

Single-cell Heterogeneity-aware Transformer-guided Multiple Instance Learning for Cancer Aneuploidy Prediction from Whole Slide Histopathology Images

Aneuploidy is a hallmark of aggressive malignancies associated with therapeutic resistance and poor survival. Measuring aneuploidy requires expensive specialized techniques that are not clinically applicable. Deep learning analysis of routine histopathology slides has revealed associations with genetic mutations. However, existing studies focus on image patches or tiles, and there is no prior work that predicts aneuploidy using single-cell analysis. Here, we present a single-cell heterogeneity-aware and transformer-guided deep learning framework to predict aneuploidy from whole slide histopathology images. First, we perform nuclei segmentation and classification to obtain individual cancer cells, which are clustered into multiple subtypes. The cell subtype distributions are computed to measure cancer cell heterogeneity. Additionally, morphological features of different cell subtypes are extracted. Further, we leverage a multiple instance learning module with Transformer, which encourages the network to focus on the most informative cancer cells. Lastly, a hybrid network is built to unify cell heterogeneity, morphology, and deep features for aneuploidy prediction. We train and validate our method on two public datasets from TCGA: lung adenocarcinoma (LUAD) and head and neck squamous cell carcinoma (HNSC), with 339 and 245 patients. Our model achieves promising performance with AUC of 0.818 (95% CI: 0.718-0.919) and 0.827 (95% CI: 0.704-0.949) on the LUAD and HNSC test sets, respectively. Through extensive ablation and comparison studies, we demonstrate the effectiveness of each component of the model and superior performance over alternative networks. In conclusion, we present a novel deep learning approach to predict aneuploidy from histopathology images, which could inform personalized cancer treatment.

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.

Genomic and immune landscape Of metastatic pheochromocytoma and paraganglioma

The mechanisms triggering metastasis in pheochromocytoma/paraganglioma are unknown, hindering therapeutic options for patients with metastatic tumors (mPPGL). Herein we show by genomic profiling of a large cohort of mPPGLs that high mutational load, microsatellite instability and somatic copy-number alteration burden are associated with ATRX/TERT alterations and are suitable prognostic markers. Transcriptomic analysis defines the signaling networks involved in the acquisition of metastatic competence and establishes a gene signature related to mPPGLs, highlighting CDK1 as an additional mPPGL marker. Immunogenomics accompanied by immunohistochemistry identifies a heterogeneous ecosystem at the tumor microenvironment level, linked to the genomic subtype and tumor behavior. Specifically, we define a general immunosuppressive microenvironment in mPPGLs, the exception being PD-L1 expressing MAML3-related tumors. Our study reveals canonical markers for risk of metastasis, and suggests the usefulness of including immune parameters in clinical management for PPGL prognostication and identification of patients who might benefit from immunotherapy.