Noninvasive Early Identification of Therapeutic Benefit from Immune Checkpoint Inhibition.

Although treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICIs) can produce remarkably durable responses, most patients develop early disease progression. Furthermore, initial response assessment by conventional imaging is often unable to identify which patients will achieve durable clinical benefit (DCB). Here, we demonstrate that pre-treatment circulating tumor DNA (ctDNA) and peripheral CD8 T cell levels are independently associated with DCB. We further show that ctDNA dynamics after a single infusion can aid in identification of patients who will achieve DCB. Integrating these determinants, we developed and validated an entirely noninvasive multiparameter assay (DIREct-On, Durable Immunotherapy Response Estimation by immune profiling and ctDNA-On-treatment) that robustly predicts which patients will achieve DCB with higher accuracy than any individual feature. Taken together, these results demonstrate that integrated ctDNA and circulating immune cell profiling can provide accurate, noninvasive, and early forecasting of ultimate outcomes for NSCLC patients receiving ICIs.

Distinct Hodgkin lymphoma subtypes defined by noninvasive genomic profiling.

The scarcity of malignant Hodgkin and Reed-Sternberg cells hampers tissue-based comprehensive genomic profiling of classic Hodgkin lymphoma (cHL). By contrast, liquid biopsies show promise for molecular profiling of cHL due to relatively high circulating tumour DNA (ctDNA) levels1-4. Here we show that the plasma representation of mutations exceeds the bulk tumour representation in most cases, making cHL particularly amenable to noninvasive profiling. Leveraging single-cell transcriptional profiles of cHL tumours, we demonstrate Hodgkin and Reed-Sternberg ctDNA shedding to be shaped by DNASE1L3, whose increased tumour microenvironment-derived expression drives high ctDNA concentrations. Using this insight, we comprehensively profile 366 patients, revealing two distinct cHL genomic subtypes with characteristic clinical and prognostic correlates, as well as distinct transcriptional and immunological profiles. Furthermore, we identify a novel class of truncating IL4R mutations that are dependent on IL-13 signalling and therapeutically targetable with IL-4Rα-blocking antibodies. Finally, using PhasED-seq5, we demonstrate the clinical value of pretreatment and on-treatment ctDNA levels for longitudinally refining cHL risk prediction and for detection of radiographically occult minimal residual disease. Collectively, these results support the utility of noninvasive strategies for genotyping and dynamic monitoring of cHL, as well as capturing molecularly distinct subtypes with diagnostic, prognostic and therapeutic potential.

Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA.

Circulating tumour DNA (ctDNA) can be used to detect and profile residual tumour cells persisting after curative intent therapy1. The study of large patient cohorts incorporating longitudinal plasma sampling and extended follow-up is required to determine the role of ctDNA as a phylogenetic biomarker of relapse in early-stage non-small-cell lung cancer (NSCLC). Here we developed ctDNA methods tracking a median of 200 mutations identified in resected NSCLC tissue across 1,069 plasma samples collected from 197 patients enrolled in the TRACERx study2. A lack of preoperative ctDNA detection distinguished biologically indolent lung adenocarcinoma with good clinical outcome. Postoperative plasma analyses were interpreted within the context of standard-of-care radiological surveillance and administration of cytotoxic adjuvant therapy. Landmark analyses of plasma samples collected within 120 days after surgery revealed ctDNA detection in 25% of patients, including 49% of all patients who experienced clinical relapse; 3 to 6 monthly ctDNA surveillance identified impending disease relapse in an additional 20% of landmark-negative patients. We developed a bioinformatic tool (ECLIPSE) for non-invasive tracking of subclonal architecture at low ctDNA levels. ECLIPSE identified patients with polyclonal metastatic dissemination, which was associated with a poor clinical outcome. By measuring subclone cancer cell fractions in preoperative plasma, we found that subclones seeding future metastases were significantly more expanded compared with non-metastatic subclones. Our findings will support (neo)adjuvant trial advances and provide insights into the process of metastatic dissemination using low-ctDNA-level liquid biopsy.

Circulating tumor DNA in advanced solid tumors: Clinical relevance and future directions.

The application of genomic profiling assays using plasma circulating tumor DNA (ctDNA) is rapidly evolving in the management of patients with advanced solid tumors. Diverse plasma ctDNA technologies in both commercial and academic laboratories are in routine or emerging use. The increasing integration of such testing to inform treatment decision making by oncology clinicians has complexities and challenges but holds significant potential to substantially improve patient outcomes. In this review, the authors discuss the current role of plasma ctDNA assays in oncology care and provide an overview of ongoing research that may inform real-world clinical applications in the near future.

Deep whole-genome ctDNA chronology of treatment-resistant prostate cancer.

Circulating tumour DNA (ctDNA) in blood plasma is an emerging tool for clinical cancer genotyping and longitudinal disease monitoring1. However, owing to past emphasis on targeted and low-resolution profiling approaches, our understanding of the distinct populations that comprise bulk ctDNA is incomplete2-12. Here we perform deep whole-genome sequencing of serial plasma and synchronous metastases in patients with aggressive prostate cancer. We comprehensively assess all classes of genomic alterations and show that ctDNA contains multiple dominant populations, the evolutionary histories of which frequently indicate whole-genome doubling and shifts in mutational processes. Although tissue and ctDNA showed concordant clonally expanded cancer driver alterations, most individual metastases contributed only a minor share of total ctDNA. By comparing serial ctDNA before and after clinical progression on potent inhibitors of the androgen receptor (AR) pathway, we reveal population restructuring converging solely on AR augmentation as the dominant genomic driver of acquired treatment resistance. Finally, we leverage nucleosome footprints in ctDNA to infer mRNA expression in synchronously biopsied metastases, including treatment-induced changes in AR transcription factor signalling activity. Our results provide insights into cancer biology and show that liquid biopsy can be used as a tool for comprehensive multi-omic discovery.

ctDNA guiding adjuvant immunotherapy in urothelial carcinoma.

Minimally invasive approaches to detect residual disease after surgery are needed to identify patients with cancer who are at risk for metastatic relapse. Circulating tumour DNA (ctDNA) holds promise as a biomarker for molecular residual disease and relapse1. We evaluated outcomes in 581 patients who had undergone surgery and were evaluable for ctDNA from a randomized phase III trial of adjuvant atezolizumab versus observation in operable urothelial cancer. This trial did not reach its efficacy end point in the intention-to-treat population. Here we show that ctDNA testing at the start of therapy (cycle 1 day 1) identified 214 (37%) patients who were positive for ctDNA and who had poor prognosis (observation arm hazard ratio = 6.3 (95% confidence interval: 4.45-8.92); P < 0.0001). Notably, patients who were positive for ctDNA had improved disease-free survival and overall survival in the atezolizumab arm versus the observation arm (disease-free survival hazard ratio = 0.58 (95% confidence interval: 0.43-0.79); P = 0.0024, overall survival hazard ratio = 0.59 (95% confidence interval: 0.41-0.86)). No difference in disease-free survival or overall survival between treatment arms was noted for patients who were negative for ctDNA. The rate of ctDNA clearance at week 6 was higher in the atezolizumab arm (18%) than in the observation arm (4%) (P = 0.0204). Transcriptomic analysis of tumours from patients who were positive for ctDNA revealed higher expression levels of cell-cycle and keratin genes. For patients who were positive for ctDNA and who were treated with atezolizumab, non-relapse was associated with immune response signatures and basal-squamous gene features, whereas relapse was associated with angiogenesis and fibroblast TGFß signatures. These data suggest that adjuvant atezolizumab may be associated with improved outcomes compared with observation in patients who are positive for ctDNA and who are at a high risk of relapse. These findings, if validated in other settings, would shift approaches to postoperative cancer care.

Bridging biological cfDNA features and machine learning approaches.

Liquid biopsies (LBs), particularly using circulating tumor DNA (ctDNA), are expected to revolutionize precision oncology and blood-based cancer screening. Recent technological improvements, in combination with the ever-growing understanding of cell-free DNA (cfDNA) biology, are enabling the detection of tumor-specific changes with extremely high resolution and new analysis concepts beyond genetic alterations, including methylomics, fragmentomics, and nucleosomics. The interrogation of a large number of markers and the high complexity of data render traditional correlation methods insufficient. In this regard, machine learning (ML) algorithms are increasingly being used to decipher disease- and tissue-specific signals from cfDNA. Here, we review recent insights into biological ctDNA features and how these are incorporated into sophisticated ML applications.

Entirely noninvasive outcome prediction in central nervous system lymphomas using circulating tumor DNA.

ABSTRACT: State-of-the-art response assessment of central nervous system lymphoma (CNSL) by magnetic resonance imaging is challenging and an insufficient predictor of treatment outcomes. Accordingly, the development of novel risk stratification strategies in CNSL is a high unmet medical need. We applied ultrasensitive circulating tumor DNA (ctDNA) sequencing to 146 plasma and cerebrospinal fluid (CSF) samples from 67 patients, aiming to develop an entirely noninvasive dynamic risk model considering clinical and molecular features of CNSL. Our ultrasensitive method allowed for the detection of CNSL-derived mutations in plasma ctDNA with high concordance to CSF and tumor tissue. Undetectable plasma ctDNA at baseline was associated with favorable outcomes. We tracked tumor-specific mutations in plasma-derived ctDNA over time and developed a novel CNSL biomarker based on this information: peripheral residual disease (PRD). Persistence of PRD after treatment was highly predictive of relapse. Integrating established baseline clinical risk factors with assessment of radiographic response and PRD during treatment resulted in the development and independent validation of a novel tool for risk stratification: molecular prognostic index for CNSL (MOP-C). MOP-C proved to be highly predictive of outcomes in patients with CNSL (failure-free survival hazard ratio per risk group of 6.60; 95% confidence interval, 3.12-13.97; P < .0001) and is publicly available at www.mop-c.com. Our results highlight the role of ctDNA sequencing in CNSL. MOP-C has the potential to improve the current standard of clinical risk stratification and radiographic response assessment in patients with CNSL, ultimately paving the way toward individualized treatment.

Acalabrutinib, venetoclax, and obinutuzumab in relapsed/refractory CLL: final efficacy and ctDNA analysis of the CLL2-BAAG trial.

ABSTRACT: The phase 2 CLL2-BAAG trial tested the measurable residual disease (MRD)-guided triple combination of acalabrutinib, venetoclax, and obinutuzumab after optional bendamustine debulking in 45 patients with relapsed/refractory chronic lymphocytic leukemia (CLL). MRD was measured by flow cytometry (FCM; undetectable MRD <10-4) in peripheral blood (PB) and circulating tumor DNA (ctDNA) using digital droplet polymerase chain reaction of variable-diversity-joining (VDJ) rearrangements and CLL-related mutations in plasma. The median number of previous treatments was 1 (range, 1-4); 18 patients (40%) had received a Bruton tyrosine kinase inhibitor (BTKi) and/or venetoclax before inclusion, 14 of 44 (31.8%) had TP53 aberrations, and 34 (75.6%) had unmutated immunoglobulin heavy-chain variable region genes. With a median observation time of 36.3 months and all patients off-treatment for a median of 21.9 months, uMRD <10-4 in PB was achieved in 42 of the 45 patients (93.3%) at any time point, including 17 of 18 (94.4%) previously exposed to venetoclax/BTKi and 13 of 14 (92.9%) with TP53 aberrations. The estimated 3-year progression-free and overall survival rates were 85.0% and 93.8%, respectively. Overall, 585 paired FCM/ctDNA samples were analyzed and 18 MRD recurrences (5 with and 13 without clinical progression) occurred after the end of treatment. Twelve samples were first detected by ctDNA, 3 by FCM, and 3 synchronously. In conclusion, time-limited MRD-guided acalabrutinib, venetoclax, and obinutuzumab achieved deep remissions in almost all patients with relapsed/refractory CLL. The addition of ctDNA-based analyses to FCM MRD assessment seems to improve early detection of relapses. This trial was registered at www.clinicaltrials.gov as #NCT03787264.

ctDNA improves prognostic prediction for patients with relapsed/refractory MM receiving ixazomib, lenalidomide, and dexamethasone.

ABSTRACT: It remains elusive how driver mutations, including those detected in circulating tumor DNA (ctDNA), affect prognosis in relapsed/refractory multiple myeloma (RRMM). Here, we performed targeted-capture sequencing using bone marrow plasma cells (BMPCs) and ctDNA of 261 RRMM cases uniformly treated with ixazomib, lenalidomide, and dexamethasone in a multicenter, prospective, observational study. We detected 24 and 47 recurrently mutated genes in BMPC and ctDNA, respectively. In addition to clonal hematopoiesis-associated mutations, varying proportion of driver mutations, particularly TP53 mutations (59.2% of mutated cases), were present in only ctDNA, suggesting their subclonal origin. In univariable analyses, ctDNA mutations of KRAS, TP53, DIS3, BRAF, NRAS, and ATM were associated with worse progression-free survival (PFS). BMPC mutations of TP53 and KRAS were associated with inferior PFS, whereas KRAS mutations were prognostically relevant only when detected in both BMPC and ctDNA. A total number of ctDNA mutations in the 6 relevant genes was a strong prognostic predictor (2-year PFS rates: 57.3%, 22.7%, and 0% for 0, 1, and ≥2 mutations, respectively) and independent of clinical factors and plasma DNA concentration. Using the number of ctDNA mutations, plasma DNA concentration, and clinical factors, we developed a prognostic index, classifying patients into 3 categories with 2-year PFS rates of 57.9%, 28.6%, and 0%. Serial analysis of ctDNA mutations in 94 cases revealed that TP53 and KRAS mutations frequently emerge after therapy. Thus, we clarify the genetic characteristics and clonal architecture of ctDNA mutations and demonstrate their superiority over BMPC mutations for prognostic prediction in RRMM. This study is a part of the C16042 study, which is registered at www.clinicaltrials.gov as #NCT03433001.

Integrating genomic features for non-invasive early lung cancer detection.

Radiologic screening of high-risk adults reduces lung-cancer-related mortality1,2; however, a small minority of eligible individuals undergo such screening in the United States3,4. The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq)5, a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent. Compared with tumour-derived mutations, clonal haematopoiesis mutations occur on longer cfDNA fragments and lack mutational signatures that are associated with tobacco smoking. Integrating these findings with other molecular features, we develop and prospectively validate a machine-learning method termed 'lung cancer likelihood in plasma' (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls. This approach achieves performance similar to that of tumour-informed ctDNA detection and enables tuning of assay specificity in order to facilitate distinct clinical applications. Our findings establish the potential of cfDNA for lung cancer screening and highlight the importance of risk-matching cases and controls in cfDNA-based screening studies.

Transposon DNA sequences facilitate the tissue-specific gene transfer of circulating tumor DNA between human cells.

The exchange of genes between cells is known to play an important physiological and pathological role in many organisms. We show that circulating tumor DNA (ctDNA) facilitates cell-specific gene transfer between human cancer cells and explain part of the mechanisms behind this phenomenon. As ctDNA migrates into the nucleus, genetic information is transferred. Cell targeting and ctDNA integration require ERVL, SINE or LINE DNA sequences. Chemically manufactured AluSp and MER11C sequences replicated multiple myeloma (MM) ctDNA cell targeting and integration. Additionally, we found that ctDNA may alter the treatment response of MM and pancreatic cancer models. This study shows that retrotransposon DNA sequences promote cancer gene transfer. However, because cell-free DNA has been detected in physiological and other pathological conditions, our findings have a broader impact than just cancer. Furthermore, the discovery that transposon DNA sequences mediate tissue-specific targeting will open up a new avenue for the delivery of genes and therapies.

Lesion Shedding Model: unraveling site-specific contributions to ctDNA.

Sampling circulating tumor DNA (ctDNA) using liquid biopsies offers clinically important benefits for monitoring cancer progression. A single ctDNA sample represents a mixture of shed tumor DNA from all known and unknown lesions within a patient. Although shedding levels have been suggested to hold the key to identifying targetable lesions and uncovering treatment resistance mechanisms, the amount of DNA shed by any one specific lesion is still not well characterized. We designed the Lesion Shedding Model (LSM) to order lesions from the strongest to the poorest shedding for a given patient. By characterizing the lesion-specific ctDNA shedding levels, we can better understand the mechanisms of shedding and more accurately interpret ctDNA assays to improve their clinical impact. We verified the accuracy of the LSM under controlled conditions using a simulation approach as well as testing the model on three cancer patients. The LSM obtained an accurate partial order of the lesions according to their assigned shedding levels in simulations and its accuracy in identifying the top shedding lesion was not significantly impacted by number of lesions. Applying LSM to three cancer patients, we found that indeed there were lesions that consistently shed more than others into the patients' blood. In two of the patients, the top shedding lesion was one of the only clinically progressing lesions at the time of biopsy suggesting a connection between high ctDNA shedding and clinical progression. The LSM provides a much needed framework with which to understand ctDNA shedding and to accelerate discovery of ctDNA biomarkers. The LSM source code has been available in the IBM BioMedSciAI Github (https://github.com/BiomedSciAI/Geno4SD).

Current and future perspectives of liquid biopsies in genomics-driven oncology.

Precision oncology seeks to leverage molecular information about cancer to improve patient outcomes. Tissue biopsy samples are widely used to characterize tumours but are limited by constraints on sampling frequency and their incomplete representation of the entire tumour bulk. Now, attention is turning to minimally invasive liquid biopsies, which enable analysis of tumour components (including circulating tumour cells and circulating tumour DNA) in bodily fluids such as blood. The potential of liquid biopsies is highlighted by studies that show they can track the evolutionary dynamics and heterogeneity of tumours and can detect very early emergence of therapy resistance, residual disease and recurrence. However, the analytical validity and clinical utility of liquid biopsies must be rigorously demonstrated before this potential can be realized.

Genome-wide cell-free DNA fragmentation in patients with cancer.

Cell-free DNA in the blood provides a non-invasive diagnostic avenue for patients with cancer1. However, characteristics of the origins and molecular features of cell-free DNA are poorly understood. Here we developed an approach to evaluate fragmentation patterns of cell-free DNA across the genome, and found that profiles of healthy individuals reflected nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles. We used this method to analyse the fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric or bile duct cancer and 245 healthy individuals. A machine learning model that incorporated genome-wide fragmentation features had sensitivities of detection ranging from 57% to more than 99% among the seven cancer types at 98% specificity, with an overall area under the curve value of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation-based cell-free DNA analyses detected 91% of patients with cancer. The results of these analyses highlight important properties of cell-free DNA and provide a proof-of-principle approach for the screening, early detection and monitoring of human cancer.

Plasma circulating tumour DNA is a better source for diagnosis and mutational analysis of IVLBCL than tissue DNA.

Diagnosis of intravascular large B-cell lymphoma (IVLBCL) is a challenge due to its heterogeneous clinical presentation and lack of specific markers. This retrospective study investigated the utility of circulating tumour DNA (ctDNA) sequencing for diagnosing IVLBCL and analysing its mutation landscape. A cohort of 34 IVLBCL patients enrolled and underwent plasma ctDNA targeted sequencing. The median plasma ctDNA concentration was 135.0 ng/mL, significantly higher than that in diffuse large B-cell lymphoma (DLBCL) controls. Correlations were found between ctDNA concentration and disease severity indicators, LDH and SF. Mutation analysis revealed frequent mutations in B-cell receptor and NF-κB signalling pathways, including MYD88 (56%), CD79B (44%), TNFAIP3 (38%) and IRF4 (29%). CNS involvement was significantly related with BCL6 and CD58 mutation. Patients with complicated hemophagocytic lymphohistiocytosis had significantly higher mutation rates in B2M. Comparison with DLBCL subtypes showed distinctive mutation profiles in IVLBCL. Moreover, plasma ctDNA detected more mutations with higher variant allele fraction than tissue DNA, suggesting its superiority in sensitivity and accessibility. Dynamic monitoring of ctDNA during treatment correlated with therapeutic responses. This study revealed the role of ctDNA in IVLBCL diagnosis, mutation analysis, and treatment monitoring, offering a promising avenue for improving patient diagnosis in this rare lymphoma subtype.

Red blood cells function as reservoirs of tumor DNA.

Novel screening techniques for early detection of lung cancer are urgently needed. Profiling circulating tumor cell-free DNA (ctDNA) has emerged as a promising tool for biopsy-free tumor genotyping. However, both the scarcity and short half-life of ctDNA substantially limit the sensitivity and clinical utility of ctDNA detection methodologies. Our discovery that red blood cells (RBCs) sequester mitochondrial DNA opens a new avenue for detecting circulating nucleic acids, as RBCs represent an unrecognized reservoir of circulating nucleic acid. Here, we show that RBCs acquire tumor DNA following coculture with lung cancer cell lines harboring Kirsten rat sarcoma viral oncogene homolog (KRAS) and epidermal growth factor receptor (EGFR) mutations. RBC-bound tumor DNA is detectable in patients with early-stage non-small cell lung cancer (NSCLC) but not in healthy controls by qPCR. Our results collectively uncover a previously unrecognized yet easily accessible reservoir of tumor DNA, offering a promising foundation for future RBC-based tumor diagnostics.NEW & NOTEWORTHY We present a novel method for lung cancer detection by revealing RBCs as a reservoir for tumor DNA, overcoming the limitations of current circulating tumor ctDNA methodologies. By demonstrating that RBCs can capture tumor DNA, including critical mutations found in lung cancer, we provide a promising, biopsy-free avenue for early cancer diagnostics. This discovery opens up exciting possibilities for developing RBC-based diagnostic tools, significantly enhancing the sensitivity and clinical utility of noninvasive cancer detection.

NSABP FB-10: a phase Ib/II trial evaluating ado-trastuzumab emtansine (T-DM1) with neratinib in women with metastatic HER2-positive breast cancer.

BACKGROUND: We previously reported our phase Ib trial, testing the safety, tolerability, and efficacy of T-DM1 + neratinib in HER2-positive metastatic breast cancer patients. Patients with ERBB2 amplification in ctDNA had deeper and more durable responses. This study extends these observations with in-depth analysis of molecular markers and mechanisms of resistance in additional patients. METHODS: Forty-nine HER2-positive patients (determined locally) who progressed on-treatment with trastuzumab + pertuzumab were enrolled in this phase Ib/II study. Mutations and HER2 amplifications were assessed in ctDNA before (C1D1) and on-treatment (C2D1) with the Guardant360 assay. Archived tissue (TP0) and study entry biopsies (TP1) were assayed for whole transcriptome, HER2 copy number, and mutations, with Ampli-Seq, and centrally for HER2 with CLIA assays. Patient responses were assessed with RECIST v1.1, and Molecular Response with the Guardant360 Response algorithm. RESULTS: The ORR in phase II was 7/22 (32%), which included all patients who had at least one dose of study therapy. In phase I, the ORR was 12/19 (63%), which included only patients who were considered evaluable, having received their first scan at 6 weeks. Central confirmation of HER2-positivity was found in 83% (30/36) of the TP0 samples. HER2-amplified ctDNA was found at C1D1 in 48% (20/42) of samples. Patients with ctHER2-amp versus non-amplified HER2 ctDNA determined in C1D1 ctDNA had a longer median progression-free survival (PFS): 480 days versus 60 days (P = 0.015). Molecular Response scores were significantly associated with both PFS (HR 0.28, 0.09-0.90, P = 0.033) and best response (P = 0.037). All five of the patients with ctHER2-amp at C1D1 who had undetectable ctDNA after study therapy had an objective response. Patients whose ctHER2-amp decreased on-treatment had better outcomes than patients whose ctHER2-amp remained unchanged. HER2 RNA levels show a correlation to HER2 CLIA IHC status and were significantly higher in patients with clinically documented responses compared to patients with progressive disease (P = 0.03). CONCLUSIONS: The following biomarkers were associated with better outcomes for patients treated with T-DM1 + neratinib: (1) ctHER2-amp (C1D1) or in TP1; (2) Molecular Response scores; (3) loss of detectable ctDNA; (4) RNA levels of HER2; and (5) on-treatment loss of detectable ctHER2-amp. HER2 transcriptional and IHC/FISH status identify HER2-low cases (IHC 1+ or IHC 2+ and FISH negative) in these heavily anti-HER2 treated patients. Due to the small number of patients and samples in this study, the associations we have shown are for hypothesis generation only and remain to be validated in future studies. Clinical Trials registration NCT02236000.

Exploring the tumor genomic landscape of aggressive prostate cancer by whole-genome sequencing of tissue or liquid biopsies.

Treatment resistance remains a major issue in aggressive prostate cancer (PC), and novel genomic biomarkers may guide better treatment selection. Circulating tumor DNA (ctDNA) can provide minimally invasive information about tumor genomes, but the genomic landscape of aggressive PC based on whole-genome sequencing (WGS) of ctDNA remains incompletely characterized. Thus, we here performed WGS of tumor tissue (n = 31) or plasma ctDNA (n = 10) from a total of 41 aggressive PC patients, including 11 hormone-naïve, 15 hormone-sensitive, and 15 castration-resistant patients. Across all variant types, we found progressively more altered tumor genomic profiles in later stages of aggressive PC. The potential driver genes most frequently affected by single-nucleotide variants or insertions/deletions included the known PC-related genes TP53, CDK12, and PTEN and the novel genes COL13A1, KCNH3, and SENP3. Etiologically, aggressive PC was associated with age-related and DNA repair-related mutational signatures. Copy number variants most frequently affected 14q11.2 and 8p21.2, where no well-recognized PC-related genes are located, and also frequently affected regions near the known PC-related genes MYC, AR, TP53, PTEN, and BRCA1. Structural variants most frequently involved not only the known PC-related genes TMPRSS2 and ERG but also the less extensively studied gene in this context, PTPRD. Finally, clinically actionable variants were detected throughout all stages of aggressive PC and in both plasma and tissue samples, emphasizing the potential clinical applicability of WGS of minimally invasive plasma samples. Overall, our study highlights the feasibility of using liquid biopsies for comprehensive genomic characterization as an alternative to tissue biopsies in advanced/aggressive PC.

Fragmentomics features of ovarian cancer.

Ovarian cancer (OC) is a major cause of cancer mortality in women worldwide. Due to the occult onset of OC, its nonspecific clinical symptoms in the early phase, and a lack of effective early diagnostic tools, most OC patients are diagnosed at an advanced stage. In this study, shallow whole-genome sequencing was utilized to characterize fragmentomics features of circulating tumor DNA (ctDNA) in OC patients. By applying a machine learning model, multiclass fragmentomics data achieved a mean area under the curve (AUC) of 0.97 (95% CI 0.962-0.976) for diagnosing OC. OC scores derived from this model strongly correlated with the disease stage. Further comparative analysis of OC scores illustrated that the fragmentomics-based technology provided additional clinical benefits over the traditional serum biomarkers cancer antigen 125 (CA125) and the Risk of Ovarian Malignancy Algorithm (ROMA) index. In conclusion, fragmentomics features in ctDNA are potential biomarkers for the accurate diagnosis of OC.