bims-tumhet Biomed News
on Tumor Heterogeneity
Issue of 2024‒08‒04
sixteen papers selected by
Sergio Marchini, Humanitas Research



  1. bioRxiv. 2024 Jul 15. pii: 2024.07.11.602772. [Epub ahead of print]
      Whole-genome doubling (WGD) is a critical driver of tumor development and is linked to drug resistance and metastasis in solid malignancies. Here, we demonstrate that WGD is an ongoing mutational process in tumor evolution. Using single-cell whole-genome sequencing, we measured and modeled how WGD events are distributed across cellular populations within tumors and associated WGD dynamics with properties of genome diversification and phenotypic consequences of innate immunity. We studied WGD evolution in 65 high-grade serous ovarian cancer (HGSOC) tissue samples from 40 patients, yielding 29,481 tumor cell genomes. We found near-ubiquitous evidence of WGD as an ongoing mutational process promoting cell-cell diversity, high rates of chromosomal missegregation, and consequent micronucleation. Using a novel mutation-based WGD timing method, doubleTime , we delineated specific modes by which WGD can drive tumor evolution: (i) unitary evolutionary origin followed by significant diversification, (ii) independent WGD events on a pre-existing background of copy number diversity, and (iii) evolutionarily late clonal expansions of WGD populations. Additionally, through integrated single-cell RNA sequencing and high-resolution immunofluorescence microscopy, we found that inflammatory signaling and cGAS-STING pathway activation result from ongoing chromosomal instability and are restricted to tumors that remain predominantly diploid. This contrasted with predominantly WGD tumors, which exhibited significant quiescent and immunosuppressive phenotypic states. Together, these findings establish WGD as an evolutionarily 'active' mutational process that promotes evolvability and dysregulated immunity in late stage ovarian cancer.
    DOI:  https://doi.org/10.1101/2024.07.11.602772
  2. Nat Rev Genet. 2024 Jul 29.
      Chromosomal instability (CIN) refers to an increased propensity of cells to acquire structural and numerical chromosomal abnormalities during cell division, which contributes to tumour genetic heterogeneity. CIN has long been recognized as a hallmark of cancer, and evidence over the past decade has strongly linked CIN to tumour evolution, metastasis, immune evasion and treatment resistance. Until recently, the mechanisms by which CIN propels cancer progression have remained elusive. Beyond the generation of genomic copy number heterogeneity, recent work has unveiled additional tumour-promoting consequences of abnormal chromosome segregation. These mechanisms include complex chromosomal rearrangements, epigenetic reprogramming and the induction of cancer cell-intrinsic inflammation, emphasizing the multifaceted role of CIN in cancer.
    DOI:  https://doi.org/10.1038/s41576-024-00761-7
  3. BMC Genomics. 2024 Jul 30. 25(1): 741
      DNA methylation is an epigenetic mechanism that regulates gene expression, and for mammals typically occurs on cytosines within CpG dinucleotides. A significant challenge for methylation detection methods is accurately measuring methylation levels within GC-rich regions such as gene promoters, as inaccuracies compromise downstream biological interpretation of the data. To address this challenge, we compared methylation levels assayed using four different Methods Enzymatic Methyl-seq (EM-seq), whole genome bisulphite sequencing (WGBS), Infinium arrays (Illumina MethylationEPIC, "EPIC"), and Oxford Nanopore Technologies nanopore sequencing (ONT) applied to human DNA. Overall, all methods produced comparable and consistent methylation readouts across the human genome. The flexibility offered by current gold standard WGBS in interrogating genome-wide cytosines is surpassed technically by both EM-seq and ONT, as their coverages and methylation readouts are less prone to GC bias. These advantages are tempered by increased laboratory time (EM-seq) and higher complexity (ONT). We further assess the strengths and weaknesses of each method, and provide recommendations in choosing the most appropriate methylation method for specific scientific questions or translational needs.
    Keywords:  DNA methylation; EM-seq; GC-rich loci; Infinium arrays; ONT; WGBS
    DOI:  https://doi.org/10.1186/s12864-024-10605-7
  4. J Pathol. 2024 Jul 31.
      Low-grade serous ovarian carcinoma (LGSC) is a rare and lethal subtype of ovarian cancer. LGSC is pathologically, biologically, and clinically distinct from the more common high-grade serous ovarian carcinoma (HGSC). LGSC arises from serous borderline ovarian tumours (SBTs). The mechanism of transformation for SBTs to LGSC remains poorly understood. To better understand the biology of LGSC, we performed whole proteome profiling of formalin-fixed, paraffin-embedded tissue blocks of LGSC (n = 11), HGSC (n = 19), and SBTs (n = 26). We identified that the whole proteome is able to distinguish between histotypes of the ovarian epithelial tumours. Proteins associated with the tumour microenvironment were differentially expressed between LGSC and SBTs. Fibroblast activation protein (FAP), a protein expressed in cancer-associated fibroblasts, is the most differentially abundant protein in LGSC compared with SBT. Multiplex immunohistochemistry (IHC) for immune markers (CD20, CD79a, CD3, CD8, and CD68) was performed to determine the presence of B cells, T cells, and macrophages. The LGSC FAP+ stroma was associated with greater abundance of Tregs and M2 macrophages, features not present in SBTs. Our proteomics cohort reveals that there are changes in the tumour microenvironment in LGSC compared with its putative precursor lesion, SBT. These changes suggest that the tumour microenvironment provides a supportive environment for LGSC tumourigenesis and progression. Thus, targeting the tumour microenvironment of LGSC may be a viable therapeutic strategy. © 2024 The Pathological Society of Great Britain and Ireland.
    Keywords:  T cells; fibroblast activation protein; fibroblasts; immunosuppression; low‐grade serous ovarian carcinoma; macrophages; multiplex IHC; regulatory T cells; serous borderline ovarian tumours; tumour microenvironment
    DOI:  https://doi.org/10.1002/path.6338
  5. Postepy Biochem. 2024 07 01. 70(2): 173-189
      There is no technique that would make a greater contribution to the development of genetics, molecular biology and medicine than DNA sequencing. For many years, the method based on enzymatic DNA synthesis developed by Frederic Sanger was the gold standard in this area. At the end of the 20th century, there was a dynamic development of next-generation sequencing (NGS) technologies, which ended the era of single gene analysis and initiated the era of genome sequencing. Despite fierce competition, one NGS technology has practically completely dominated the global market. In the article, we present our own review of DNA sequencing methods, starting from the Sanger method to high-throughput second- and third-generation sequencing technologies, with particular emphasis on those that have achieved commercial success. We present their short history, principles of operation, technical possibilities, applications and limitations. In the summary, we reveal how much human genome sequencing costs at the current stage of the genomic revolution and outline the prospects for further development of genomics.
    DOI:  https://doi.org/10.18388/pb.2021_534
  6. Int Immunopharmacol. 2024 Jul 31. pii: S1567-5769(24)01289-X. [Epub ahead of print]140 112768
      DNA damage is typically caused during cell growth by DNA replication stress or exposure to endogenous or external toxins. The accumulation of damaged DNA causes genomic instability, which is the root cause of many serious disorders. Multiple cellular organisms utilize sophisticated signaling pathways against DNA damage, collectively known as DNA damage response (DDR) networks. Innate immune responses are activated following cellular abnormalities, including DNA damage. Interestingly, recent studies have indicated that there is an intimate relationship between the DDR network and innate immune responses. Diverse kinds of cytosolic DNA sensors, such as cGAS and STING, recognize damaged DNA and induce signals related to innate immune responses, which link defective DDR to innate immunity. Moreover, DDR components operate in immune signaling pathways to induce IFNs and/or a cascade of inflammatory cytokines via direct interactions with innate immune modulators. Consistently, defective DDR factors exacerbate the innate immune imbalance, resulting in severe diseases, including autoimmune disorders and tumorigenesis. Here, the latest progress in understanding crosstalk between the DDR network and innate immune responses is reviewed. Notably, the dual function of innate immune modulators in the DDR network may provide novel insights into understanding and developing targeted immunotherapies for DNA damage-related diseases, even carcinomas.
    Keywords:  Adaptive immune responses; DNA damage response (DDR); IFN; Innate immune responses; cGAS-STING
    DOI:  https://doi.org/10.1016/j.intimp.2024.112768
  7. Bioinformatics. 2024 Jul 27. pii: btae454. [Epub ahead of print]
      MOTIVATION: Copy number alterations (CNAs) play an important role in disease progression, especially in cancer. Single-cell DNA sequencing (scDNA-seq) facilitates the detection of CNAs of each cell that is sequenced at a shallow and uneven coverage. However, the state-of-the-art CNA detection tools based on scDNA-seq are still subject to genome-wide errors due to the wrong estimation of the ploidy.RESULTS: We developed SCCNAInfer, a computational tool that utilizes the subclonal signal inside the tumor cells to more accurately infer each cell's ploidy and CNAs. Given the segmentation result of an existing CNA detection method, SCCNAInfer clusters the cells, infers the ploidy of each subclone, refines the read count by bin clustering, and accurately infers the CNAs for each cell. Both simulated and real datasets show that SCCNAInfer consistently improves upon the state-of-the-art CNA detection tools such as Aneufinder, Ginkgo, SCOPE and SeCNV.
    AVAILABILITY AND IMPLEMENTATION: SCCNAInfer is freely available at https://github.com/compbio-mallory/SCCNAInfer.
    SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
    DOI:  https://doi.org/10.1093/bioinformatics/btae454
  8. Lancet Oncol. 2024 Aug;pii: S1470-2045(24)00401-7. [Epub ahead of print]25(8): 945
      
    DOI:  https://doi.org/10.1016/S1470-2045(24)00401-7
  9. Cell Rep Med. 2024 Jul 25. pii: S2666-3791(24)00380-X. [Epub ahead of print] 101666
      Epithelial ovarian cancer (EOC) is the deadliest women's cancer and has a poor prognosis. Early detection is the key for improving survival (a 5-year survival rate in stage I/II is over 70% compared to that of 25% in stage III/IV) and can be achieved through methylation markers from circulating cell-free DNA (cfDNA) using a liquid biopsy. In this study, we first identify top 500 EOC markers differentiating EOC from healthy female controls from 3.3 million methylome-wide CpG sites and validated them in 1,800 independent cfDNA samples. We then utilize a pretrained AI transformer system called MethylBERT to develop an EOC diagnostic model which achieves 80% sensitivity and 95% specificity in early-stage EOC diagnosis. We next develop a simple digital droplet PCR (ddPCR) assay which archives good performance, facilitating early EOC detection.
    Keywords:  cfDNA; early cancer detection; liquid biopsy; methylation; neuronal network; ovarian cancer; transformer
    DOI:  https://doi.org/10.1016/j.xcrm.2024.101666
  10. BMC Med. 2024 Jul 29. 22(1): 310
      BACKGROUND: Uterine corpus endometrial carcinoma (UCEC) is a prevalent gynecologic malignancy with a favorable prognosis if detected early. However, there is a lack of accurate and reliable early detection tests for UCEC. This study aims to develop a precise and non-invasive diagnostic method for UCEC using circulating cell-free DNA (cfDNA) fragmentomics.METHODS: Peripheral blood samples were collected from all participants, and cfDNA was extracted for analysis. Low-coverage whole-genome sequencing was performed to obtain cfDNA fragmentomics data. A robust machine learning model was developed using these features to differentiate between UCEC and healthy conditions.
    RESULTS: The cfDNA fragmentomics-based model showed high predictive power for UCEC detection in training (n = 133; AUC 0.991) and validation cohorts (n = 89; AUC 0.994). The model manifested a specificity of 95.5% and a sensitivity of 98.5% in the training cohort, and a specificity of 95.5% and a sensitivity of 97.8% in the validation cohort. Physiological variables and preanalytical procedures had no significant impact on the classifier's outcomes. In terms of clinical benefit, our model would identify 99% of Chinese UCEC patients at stage I, compared to 21% under standard care, potentially raising the 5-year survival rate from 84 to 95%.
    CONCLUSION: This study presents a novel approach for the early detection of UCEC using cfDNA fragmentomics and machine learning showing promising sensitivity and specificity. Using this model in clinical practice could significantly improve UCEC management and control, enabling early intervention and better patient outcomes. Further optimization and validation of this approach are warranted to establish its clinical utility.
    Keywords:  Early detection; Endometrial carcinoma; Fragmentomics; cfDNA
    DOI:  https://doi.org/10.1186/s12916-024-03531-8
  11. J Natl Cancer Inst. 2024 Aug 01. pii: djae179. [Epub ahead of print]
      Detection of cell-free circulating tumor DNA (ctDNA) from solid tumors is a fast-evolving field with significant potential for improving patient treatment outcomes. The spectrum of applications for ctDNA assays is broad and includes very diverse intended uses that will require different strategies to demonstrate utility. On September 14-15, 2023, the National Cancer Institute held an in-person workshop in Rockville, MD entitled "ctDNA in Cancer Treatment and Clinical Care". The goal of the workshop was to examine what is currently known and what needs to be determined for various ctDNA liquid biopsy use cases related to treatment and management of patients with solid tumors and to explore how the community can best assess the value of ctDNA assays and technology. Additionally, new approaches were presented that may show promise in the future. The information exchanged in this workshop will provide the community with a better understanding of this field and its potential to affect and benefit decision-making in the treatment of patients with solid tumors.
    DOI:  https://doi.org/10.1093/jnci/djae179
  12. Rambam Maimonides Med J. 2024 Jul 30. 15(3):
      OBJECTIVE: Medical decision-making is often uncertain. The positive predictive value (PPV) and negative predictive value (NPV) are conditional probabilities characterizing diagnostic tests and assessing diagnostic interventions in clinical medicine and epidemiology. The PPV is the probability that a patient has a specified disease, given a positive test result for that disease. The NPV is the probability that a patient does not have the disease, given a negative test result for that disease. Both values depend on disease incidence or prevalence, which may be highly uncertain for unfamiliar diseases, epidemics, etc. Probability distributions for this uncertainty are usually unavailable. We develop a non-probabilistic method for interpreting PPV and NPV with uncertain prevalence.METHODS: Uncertainty in PPV and NPV is managed with the non-probabilistic concept of robustness in info-gap theory. Robustness of PPV or NPV estimates is the greatest uncertainty (in prevalence) at which the estimate's error is acceptable.
    RESULTS: Four properties are demonstrated. Zeroing: best estimates of PPV or NPV have no robustness to uncertain prevalence; best estimates are unreliable for interpreting diagnostic tests. Trade-off: robustness increases as error increases; this trade-off identifies robustly reliable error in PPV or NPV. Preference reversal: sometimes sub-optimal PPV or NPV estimates are more robust to uncertain incidence or prevalence than optimal estimates, motivating reversal of preference from the putative optimum to the sub-optimal estimate. Trade-off between specificity and robustness to uncertainty: the robustness increases as test-specificity decreases. These four properties underlie the interpretation of PPV and NPV.
    CONCLUSIONS: The PPV and NPV assess diagnostic tests, but are sensitive to lack of knowledge that generates non-probabilistic uncertain prevalence and must be supplemented with robustness analysis. When uncertainties abound, as with unfamiliar diseases, assessing robustness is critical to avoiding erroneous decisions.
    DOI:  https://doi.org/10.5041/RMMJ.10527
  13. Clin Cancer Res. 2024 Jul 30.
      OBJECTIVE: To compare the effectiveness of PARP inhibitor maintenance therapy (mPARPi) in real-world practice by biomarker status (BRCA1/2 alterations [BRCAalt] and a homologous recombination deficiency signature [HRDsig]) in advanced ovarian cancer (OC).METHODS: Patients with OC receiving 1st-line platinum-based chemotherapy and either mPARPi or no maintenance were included. Patient data was obtained by a US-based de-identified OC clinico-genomic database, from ~280 US cancer clinics (01/2015-03/2023). Real-world progression-free survival (rwPFS) and overall survival (rwOS) were compared by biomarker status using Cox models, weighted by propensity scores.
    RESULTS: Of 673 patients, 160 received mPARPi [31.2% BRCAalt and 51.9% HRDsig(+)] and 513 no maintenance [15.6% BRCAalt and 34.1% HRDsig(+)]. BRCAalt patients receiving mPARPi vs. no maintenance had favorable rwPFS (HR 0.48, 95%CI 0.26-0.87, p=0.0154), as did BRCA wild-type (wt) (HR 0.76, 95%CI 0.57-1.01, p=0.0595). Favorable rwOS was not observed with mPARPi for BRCAalt or BRCAwt. HRDsig(+) patients receiving mPARPi vs. no maintenance had favorable rwPFS (HR 0.36, 95%CI 0.24-0.55, p <0.001) and numerically favorable rwOS (HR 0.46, 95%CI 0.21-1.14, p=0.0561). No differences were observed for HRDsig(-). mPARPi treatment interaction was observed for HRDsig(+) vs. HRDsig(-) (rwPFS p<0.001 / rwOS p=0.016) but not for BRCAalt vs. BRCAwt. Patients BRCAwt/HRDsig(+) receiving mPARPi had favorable rwPFS (HR 0.40, 95%CI 0.22-0.72, p=0.003), while no difference was observed for BRCAwt/HRDsig(-).
    CONCLUSIONS: HRDsig predicted benefit of mPARPi better than BRCAalt. HRDsig(+) patients had favorable outcomes, even among BRCAwt patients, while HRDsig(-) patients showed no enrichment for benefit with mPARPi. HRDsig might predict benefit from mPARPi regardless of BRCAalt status.
    DOI:  https://doi.org/10.1158/1078-0432.CCR-24-1225
  14. Clin Cancer Res. 2024 Aug 02.
      PURPOSE: Early detection of neurofibromatosis type 1 (NF1) associated peripheral nerve sheath tumors (PNST) informs clinical decision-making, enabling early definitive treatment and potentially averting deadly outcomes. Here, we describe a cell-free DNA (cfDNA) fragmentomic approach which distinguishes non-malignant, pre-malignant and malignant forms of PNST in cancer predisposition syndrome NF1.EXPERIMENTAL DESIGN: cfDNA was isolated from plasma samples of a novel cohort of 101 NF1 patients and 21 healthy controls and underwent whole genome sequencing. We investigated diagnosis-specific signatures of copy number alterations (CNA) with in silico size selection as well as well as fragment profiles. Fragmentomics were analyzed using complementary feature types: bin-wise fragment size ratios, end-motifs, and fragment non-negative matrix factorization (NMF) signatures.
    RESULTS: The novel cohort of NF1 patients validated that our previous cfDNA CNA-based approach identifies malignant peripheral nerve sheath tumor (MPNST) but cannot distinguish among benign and premalignant states. Fragmentomic methods were able to differentiate pre-malignant states including atypical neurofibromas (AN). Fragmentomics also adjudicated AN cases suspicious for MPNST, correctly diagnosing samples noninvasively, which could have informed clinical management.
    CONCLUSIONS: Novel cfDNA fragmentomic signatures distinguish atypical neurofibromas from benign plexiform neurofibromas and malignant peripheral nerve sheath tumors, enabling more precise clinical diagnosis and management. This study pioneers the early detection of malignant and premalignant peripheral nerve sheath tumors in NF1 and provides a blueprint for de-centralizing non-invasive cancer surveillance in hereditary cancer syndromes.
    DOI:  https://doi.org/10.1158/1078-0432.CCR-24-0797
  15. Cell Rep Med. 2024 Jul 29. pii: S2666-3791(24)00378-1. [Epub ahead of print] 101664
      In this study, we develop a stacked ensemble model that utilizes cell-free DNA (cfDNA) fragmentomics for the early detection of esophageal squamous cell carcinoma (ESCC). This model incorporates four distinct fragmentomics features derived from whole-genome sequencing (WGS) and advanced machine learning algorithms for robust analysis. It is validated across both an independent validation cohort and an external cohort to ensure its generalizability and effectiveness. Notably, the model maintains its robustness in low-coverage sequencing environments, demonstrating its potentials in clinical settings with limited sequencing resources. With its remarkable sensitivity and specificity, this approach promises to significantly improve the early diagnosis and management of ESCC. This study represents a substantial step forward in the application of cfDNA fragmentomics in cancer diagnostics, emphasizing the need for further research to fully establish its clinical efficacy.
    Keywords:  cell-free DNA; early detection; esophageal cancer; machine learning; whole-genome sequencing
    DOI:  https://doi.org/10.1016/j.xcrm.2024.101664
  16. Thorac Cancer. 2024 Jul 30.
      BACKGROUND: Homologous recombination deficiency (HRD) is a biomarker that predicts response to ovarian cancer treatment with poly (ADP-ribose) polymerase (PARP) inhibitors or breast cancer treatment with first-line platinum-based chemotherapy. However, there are few studies on the prognosis of lung cancer patients treated with immune checkpoint inhibitor (ICI) therapy using HRD as a biomarker.METHODS: We studied the relationship between HRD status and the effectiveness of first-line ICI-based therapy in EGFR/ALK wild-type metastatic non-small cell lung cancer patients (NSCLC) patients.
    RESULTS: This study included 22 treatment naïve NSCLC patients. The HRD score ranged from -26.37 to 92.34, with an average of 24.57. Based on analysis of the progression-free survival (PFS) data from the included NSCLC patients, threshold traversal was carried out. HRD (+) was defined as an HRD score of 31 or higher. Kaplan-Meier PFS survival analysis showed prolonged median PFS (mPFS) in NSCLC patients with HRD (+) versus HRD (-) (N/A vs. 7.0 ms, log-rank p = 0.029; HR 0.20, 95% CI: 0.04-0.96, likelihood-ratio p = 0.03). In patients with PD-L1 TPS ≥50% and HRD score ≥31 (co-status high), the mPFS was temporarily not reached during the follow-up period. In patients with PD-L1 TPS <1% and HRD score <31, the mPFS was 3 ms. Cox regression analysis showed that the hazard ratio of the co-status was 0.14 (95% CI: 0.04-0.54), which was a good prognostic factor, and the prognostic effect of co-status was better than that of HRD score alone.
    CONCLUSION: The HRD status can be identified as an independent significance in NSCLC patients treated with first-line ICI-based therapy.
    Keywords:  HRD; immunotherapy; non‐small cell lung cancer
    DOI:  https://doi.org/10.1111/1759-7714.15408