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Early Detection of Maternal Cancer Through Prenatal cfDNA Analysis: A New Era in Medicine

Early Detection of Maternal Cancer Through Prenatal cfDNA Analysis: A New Era in Medicine
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Prenatal genetic screening is an important technology that provides pregnant people with critical information about both fetal and maternal health. Cell-free DNA (cfDNA) analysis is a highly sensitive method for detecting fetal chromosomal abnormalities and has reduced the need for invasive procedures by 50-70%. However, an unexpected additional benefit has emerged in clinical use: some genomic abnormalities detected by cfDNA analysis may indicate hidden maternal cancers.

Published on 4 December 2024 in NEJM, this research is among the first comprehensive studies to systematically examine cfDNA analysis's potential to detect maternal cancers. Its main aim was to identify biomarkers linking chromosomal abnormalities detected during cfDNA analysis to malignant and benign conditions and to propose a standardized screening protocol for these individuals.


A Process Beginning with Abnormal or Unreportable NIPT Results

This study is part of the IDENTIFY project conducted by the US National Institutes of Health (NIH). It examined cfDNA analysis reports from 12 laboratories in North America.

Participants were selected according to the following criteria:

  • Participants were selected from people whose noninvasive prenatal testing (NIPT) produced abnormal or unreportable cfDNA analysis results.
  • This generally includes cases in which fetal aneuploidy cannot be assessed or results are incompatible with a viable fetus.
  • People who were pregnant or within two years after giving birth.
  • People without a cancer diagnosis.

NIPT (Noninvasive Prenatal Testing) is a noninvasive genetic screening test that analyzes cell-free DNA (cfDNA) in maternal blood to detect fetal chromosomal abnormalities such as Down syndrome (Trisomy 21), Edwards syndrome (Trisomy 18), and Patau syndrome (Trisomy 13). It can generally be performed from the 10th week of pregnancy and reduces the need for invasive procedures such as amniocentesis.

Standardized Cancer Screening Protocol

The following methods were used to detect cancer in participants:

  1. Rapid Whole-Body MRI: Noncontrast imaging, known to be safe during pregnancy, was preferred. Contrast-enhanced MRI was used in nonpregnant individuals.
  2. Laboratory Tests: Complete blood count, metabolic panel, and tumor markers (such as CA-125, CEA, and CA 19-9).
  3. cfDNA Analysis: Genome-wide DNA analysis was performed using a standardized protocol.
  4. Physical Examination: Participants' medical and family histories were reviewed, and oncological symptoms were assessed.
  5. Extended Genetic Counseling: All participants received genetic counseling.

The primary aim was to confirm cancer diagnoses through the screening protocol. Secondary analyses evaluated the role of genomic patterns observed in cfDNA analysis in identifying malignancy risk.


How Was cfDNA Analysis Performed?

cfDNA analysis was performed on maternal peripheral blood , not amniotic fluid. This is a common prenatal screening method, preferred because it is noninvasive.

The analysis involved the following steps:

  1. Blood Sample Collection: Maternal peripheral blood was collected in specialized tubes, such as Streck tubes, designed to preserve cell-free DNA stability.
  2. Plasma Separation: The collected blood sample was centrifuged to separate the plasma. cfDNA is present in this plasma fraction.
  3. Cell-Free DNA Isolation: cfDNA was extracted from plasma. 90% is maternal, usually originating from the hematopoietic system, and 10% is fetal, originating through the placenta.
  4. Library Preparation and Sequencing: The isolated cfDNA was analyzed on a genome-wide platform using massively parallel sequencing methods. This approach uses bioinformatic algorithms to detect abnormalities such as chromosomal gains or losses.

This noninvasive technique can provide information about both fetal health, such as aneuploidy screening, and maternal health, such as hidden cancer detection. Its low risk compared with invasive methods such as amniocentesis is a major advantage, particularly for pregnant people.


Findings: Unexpected Realities

Overview of Cancer Diagnoses

  • Cancer was detected in 48.6% of the 107 participants (52 people).
  • The most common diagnoses were:
    • Lymphoma (59.6%): 20 Hodgkin and 11 non-Hodgkin lymphomas.
    • Colorectal Cancer (17.3%): Detected at an advanced stage in most participants.
    • Breast Cancer (7.7%): Cancer was detected at an early stage in one of the 4 people diagnosed.
    • Rare Cancers: Rare cases included pancreatic cancer, adrenocortical carcinoma, Ewing sarcoma, and kidney cancer.

55.8% of participants (29 people) were asymptomatic, while 25% (13 people) attributed their symptoms to pregnancy, for example, interpreting epigastric pain as reflux. Clinical signs had gone unrecognized in the remaining 19.2%.

NOTE: The high cancer rate in this study (48.6%) reflects the fact that participants were not randomly selected from the general population. The study's specific design targeted a particular group with suspected cancer. Rather than cancer prevalence in the general population, the study aimed to assess the cancer rate in people with abnormalities detected by cfDNA analysis .

Genomic Patterns in cfDNA Analysis

The patterns observed in cfDNA analysis played a critical role in distinguishing malignant from benign conditions. The image below shows the six main genomic patterns identified during the research:

Genomic patterns in cfDNA analysis played a critical role in distinguishing malignant from benign conditions

Explanation of the Charts:

  1. Normal (Figure A): A pattern consistent with a euploid fetus.
  2. Chromosomal Gains and Losses (Figure B): Observed in 95.9% of people diagnosed with cancer.
  3. Chromosomal Gains (Figure C): Usually indicate benign conditions, such as confined placental mosaicism.
  4. Chromosomal Losses (Figure D): Detected in people with fibroids.
  5. Maternal Copy Number Variants (Figure E): Associated with clonal hematopoiesis.
  6. Borderline Abnormal (Figure F): Nonspecific patterns that nevertheless carry a potential risk of malignancy.

Cancer Detection with MRI

MRI stood out as one of the most effective methods for evaluating people with abnormal cfDNA results:

  • Sensitivity: 98.0%
  • Specificity: 88.5%

The image below shows characteristic MRI findings for different cancers and benign conditions:

characteristic MRI findings for different cancers and benign conditions

Explanation:

  1. Lymphoma (Panel 1): Mediastinal adenopathy and lung nodules were observed.
  2. Breast Cancer (Panel 2): A breast mass and enlarged axillary lymph nodes were detected.
  3. Adrenocortical Carcinoma (Panel 3): An adrenal mass and retroperitoneal adenopathy were detected.
  4. Fibroid (Panel 4): A giant uterine fibroid and an intrauterine fetus were imaged.

Discussion: A New Perspective on Clinical Management

Cancer Detection and Management

The study showed that prompt, comprehensive cancer screening is vital for people with abnormal cfDNA results. Multiple chromosomal gains and losses, in particular, were associated with a high risk of malignancy.

Comparison of Clinical Test Performance

Clinical Test
Whole-Body MRI (N=101)
Serum Tumor Markers (N=103)
CEA, CA 15-3, CA 19-9 (N=103)
True positives (number) 48 34 24
True negatives (number) 46 39 48
False positives (number) 6 14 5
False negatives (number) 1 16 26
Area under the ROC curve (%) 93.2 70.8 69.3
Sensitivity (%) 98 68 48
Specificity (%) 88.5 73.6 90.6
Positive predictive value (%) 88.9 70.8 82.8
Negative predictive value (%) 97.9 70.9 64.9

Additional Notes on the Table:

  1. True Positive: Radiological or laboratory findings indicating possible cancer in participants diagnosed with cancer.
  2. False Positive: Radiological or laboratory findings falsely suggesting cancer in participants who were not diagnosed with cancer.
  3. Whole-Body MRI: It could not be completed in 6 participants. Targeted imaging was performed in 3 cancer patients. Another 3 participants without a cancer diagnosis—one with a fetal finding, one with a placental finding, and one with a false-positive cfDNA result—could not complete MRI.
  4. Serum Tumor Markers: CA-125, CA 15-3, CA 27.29, CA 19-9, and carcinoembryonic antigen (CEA) were measured. Any tumor marker exceeding the normal reference range was considered "suspicious for malignancy." Tumor markers were not analyzed in two cancer patients and two participants without cancer.
  5. CEA, CA 19-9, and CA 15-3: These markers were evaluated separately because they are known not to be substantially affected during pregnancy. They were not analyzed in two cancer patients and two participants without cancer.
  6. Stool Sample: A total of 27 participants, including one diagnosed with colon cancer, could not provide a stool sample.

However, several challenges stand out:

  • False Positives: Some abnormal cfDNA results, such as monosomies alone, may be associated with benign conditions.
  • Delayed Intervention: In most participants, the interval between cfDNA analysis and cancer screening was 9.6 weeks (2-114 weeks).

Differences and the Need for Standardization

Differences in technologies and reporting methods among US commercial laboratories complicate clinical management. International standards could address these problems.


Conclusion and Recommendations

cfDNA analysis and rapid whole-body MRI can provide critical information about maternal as well as fetal health in prenatal screening. The study highlights these methods' importance in the early diagnosis of hidden cancers in pregnant people. Recommendations include:

  1. Rapid Intervention Protocols: A prompt, standardized screening protocol should be developed for people with abnormal cfDNA results.
  2. Education and Awareness: Healthcare professionals' awareness of the potential implications of cfDNA analysis should be increased.
  3. Technology Development: Bioinformatic algorithms used in cfDNA analysis should be optimized to detect malignancy-specific patterns more sensitively.

This study provides a strong example of how genetic technologies can revolutionize healthcare. Further studies in larger populations may increase the generalizability of these findings and facilitate their integration into clinical practice.

Sources

Turriff, A. E., Annunziata, C. M., Malayeri, A. A., Redd, B., Pavelova, M., Goldlust, I. S., Rajagopal, P. S., Lin, J., & Bianchi, D. W. (2024). Prenatal cfDNA Sequencing and Incidental Detection of Maternal Cancer. New England Journal of Medicine, 391(22), 2123-2132. https://doi.org/10.1056/NEJMoa2401029
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