bims-tumhet Biomed News
on Tumor Heterogeneity
Issue of 2022‒08‒28
three papers selected by
Sergio Marchini
Humanitas Research


  1. Nat Commun. 2022 Aug 23. 13(1): 4953
      Mutational signatures accumulate in somatic cells as an admixture of endogenous and exogenous processes that occur during an individual's lifetime. Since dividing cells release cell-free DNA (cfDNA) fragments into the circulation, we hypothesize that plasma cfDNA might reflect mutational signatures. Point mutations in plasma whole genome sequencing (WGS) are challenging to identify through conventional mutation calling due to low sequencing coverage and low mutant allele fractions. In this proof of concept study of plasma WGS at 0.3-1.5x coverage from 215 patients and 227 healthy individuals, we show that both pathological and physiological mutational signatures may be identified in plasma. By applying machine learning to mutation profiles, patients with stage I-IV cancer can be distinguished from healthy individuals with an Area Under the Curve of 0.96. Interrogating mutational processes in plasma may enable earlier cancer detection, and might enable the assessment of cancer risk and etiology.
    DOI:  https://doi.org/10.1038/s41467-022-32598-1
  2. Front Oncol. 2022 ;12 942735
      Purpose: Cervical smear samples are easily obtainable and may effectively reflect the tumor microenvironment in gynecological cancers. Therefore, we investigated the feasibility of genomic profiling based on tumor DNA analysis from cervical smear samples from endometrial cancer patients.Materials and methods: Preoperative cervical smear samples were obtained via vaginal sampling in 50 patients, including 39 with endometrial cancer and 11 with benign uterine disease. Matched blood samples were obtained simultaneously. Genomic DNA (gDNA) from cervical smear and/or cell-free DNA from whole blood were extracted and sequenced using the Pan100 panel covering 100 endometrial cancer-related genes.
    Results: Cervical swab-based gDNA analysis detected cancer with 67% sensitivity and 100% specificity, showing a superior performance compared to that of the matched blood or Pap smear tests. Cervical swab-based gDNA effectively identified patients with loss of MSH2 or MSH6 and aberrant p53 expression based on immunohistochemistry. Genomic landscape analysis of cervical swab-based gDNA identified PTEN, PIK3CA, TP53, and ARID1A as the most frequently altered genes. Furthermore, 26 endometrial cancer patients could be classified according to the Proactive Molecular Risk Classifier for Endometrial Cancer.
    Conclusion: Cervical swab-based gDNA test showed an improved detection potential and allowed the classification of patients, which has both predictive and prognostic implications.
    Keywords:  Papanicolaou (PAP) smear; circulating tumor DNA (ctDNA); endometrial cancer; immunohistochemistry; molecular classification and biomarkers
    DOI:  https://doi.org/10.3389/fonc.2022.942735
  3. Clin Transl Med. 2022 Aug;12(8): e1014
      BACKGROUND: Cancer cell-specific variation and circulating tumour DNA (ctDNA) methylation are promising biomarkers for non-invasive cancer detection and molecular classification. Nevertheless, the applications of ctDNA to the early detection and screening of cancer remain highly challenging due to the scarcity of cancer cell-specific ctDNA, the low signal-to-noise ratio of DNA variation, and the lack of non-locus-specific DNA methylation technologies.METHODS: We enrolled three cohorts of breast cancer (BC) patients from two hospitals in China (BC: n = 123; healthy controls: n = 40). We developed a ctDNA whole-genome bisulfite sequencing technology employing robust trace ctDNA capture from up to 200 μL plasma, mini-input (1 ng) library preparation, unbiased genome-wide coverage and comprehensive computational methods.
    RESULTS: A diagnostic signature comprising 15 ctDNA methylation markers exhibited high accuracy in the early (area under the curve [AUC] of 0.967) and advanced (AUC of 0.971) BC stages in multicentre patient cohorts. Furthermore, we revealed a ctDNA methylation signature that discriminates estrogen receptor status (Training set: AUC of 0.984 and Test set: AUC of 0.780). Different cancer types, including hepatocellular carcinoma and lung cancer, could also be well distinguished.
    CONCLUSIONS: Our study provides a toolset to generate unbiased whole-genome ctDNA methylomes with a minimal amount of plasma to develop highly specific and sensitive biomarkers for the early diagnosis and molecular subtyping of cancer.
    Keywords:  DNA methylation; cancer early detection; circulating tumour DNA; epigenetic biomarkers; liquid biopsy; whole-genome bisulfite sequencing
    DOI:  https://doi.org/10.1002/ctm2.1014