FreeCME

PAP 3.0 — The Next Generation

August 1, 2013
/ Print / Reprints /
| Share More
/ Text Size+

By Robert L. Coleman, MD, Professor, University of Texas; M.D. Anderson Cancer Center, Houston. Dr. Coleman reports no financial relationships relevant to this field of study.

Synopsis: A new technique of evaluating liquid-based Pap smears has been developed to identify confirmed disease-specific mutations in patients with uterine and ovarian cancers. The new technique identified most uterine and some ovarian cancers and importantly,
produced no false positive screens among normal,
noncancer controls.

Source: Kinde I, et al. Evaluation of DNA from the Papanicolaou test to detect ovarian and endometrial cancers. Sci Transl Med 2013;5:167ra4.

Since the introduction of the papanicolaou (pap) smear for cervix cancer screening, mortality rates from this disease have plummeted. Initial ascertainment of cells came from cervix lavage. This was quickly modified by direct sampling and remains a staple of use throughout the world. Advances in collection/preservation technology brought the opportunity to perform liquid-based collection, automation, and an iterative modification in diagnosis/triage with the performance of HPV testing. Since abnormal glandular cells from ovarian and uterine origin are occasionally found in cervical smears, the authors hypothesized that next-generation sequencing technology could provide the next transformative iteration of the Pap smear by identifying, with high confidence, mutational profiling in cancer present in the upper genital tract. To do this, they developed a panel of genes commonly mutated in endometrial and ovarian cancers by performing whole-exome sequencing on 22 endometrial cancers and interrogating known whole-exome sequencing datasets for other ovarian and endometrial cancers. They then used this panel (which included common abnormalities such as P53, PI3K pathway aberrations [PTEN, PIK3CA, Akt], MAPK pathway aberrations [BRAF, NRAS, KRAS], and CTNNB1) to search for mutations in 24 endometrial and 22 ovarian cancers. They identified at least one mutation in all 46 tumor samples. Then, from the corresponding liquid Pap smear specimens, they used a massively parallel sequencing method to look for the same mutations in cells and DNA in the fluid and cell pellet. Remarkably, they identified 100% of the endometrial cancers and 41% of ovarian cancers. To confirm these observations, they developed a sequence-based method to look for mutations in 12 genes in a single-liquid Pap smear specimen without previous knowledge of the tumor’s genotype. When applied to 14 positive cases, the expected tumor-specific mutations were identified. The test, called PapGene, also provided quantitative results for mutation frequencies and, importantly, was negative in all noncancer control patients. The authors concluded that mutational profiling can be accomplished via Pap testing and, although preliminary, could be used in early detection models and surveillance of disease.

Commentary

The explosion of knowledge regarding cancer biology is largely based on understanding how genomic alterations drive disease. In these investigations, serial and cumulative gene expression and loss of expression have been identified and have provided unprecedented insight into the character of disease, particularly in diseases that share morphology but not natural history. Much of this progress is fueled by the global effort to sequence the human genome and individual tumors.1,2 The current article incorporates the sophistication of next-generation sequencing with "leftover" DNA hidden in the specimen material from liquid-based Pap smears. The hypothesis is rational since, albeit with low specificity and sensitivity, abnormal glandular cells for extra-cervical origin have been found in routine Pap testing. The ability to identify DNA is already available for HPV, as well are multiplex systems to analyze in parallel multiple tissue samples for multiple genetic aberrations. PapGene combines these two advances and demonstrates, preliminarily, that genomic alterations and mutations that present within specific cancers can be identified in shed material resting in the endocervix, particularly for endometrial cancers.

As is well known, the success of any screening modality lies on its ease of administration on a large-scale audience, reproducibility between and within testing facilities, low cost, patient acceptability, high positive predictive value, and optimal sensitivity and specificity, so as to not harm patients without disease. Endometrial and ovarian cancer screening efforts are plagued by deficiencies in several of these tenets. The current test is a step in the right direction, provided it can be validated in the broader population. In addition, there are several other considerations that will need development, including increasing the detection rate among the ovarian cancer cases. The authors suggest that endometrial aspiration may be a way to collect more proximal tissue, but this has negative implications on patient acceptance and cost. The genomic portfolio could be greatly expanded, particularly as the body of knowledge grows, but this is challenged by cost and external validity. Finally, gene events occur in a continuum of the cancer process; for a diagnostic such as this to work, we would be most interested in early events where early-stage or preinvasive disease can be identified and acted upon to change the natural history. While these challenges await further exploration, the novel technology is an important contribution to the growing portfolio of non-invasive, next-generation screening efforts (such as circulating cell-free DNA)3combining our best understanding of the genome and how to best leverage its measurable elements.

References

  1. Cancer Genome Atlas Research Network, et al. Integrated genomic characterization of endometrial carcinoma. Nature 2013;497:67-73.
  2. Cancer Genome Atlas Research Network. Integrated genomic analyses of ovarian carcinoma. Nature 2011;474:609-615.
  3. Murtaza M, et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 2013;497:108-112.
  4. Shaw JA, et al. Genomic analysis of circulating cell-free DNA infers breast cancer dormancy. Genome Res 2012;22:220-231.